1 Introduction

What predicts start-up success? As six entrepreneurial-minded students from LBS, we wanted to understand better how start-up success can be predicted. Which industry receive higher funding and which locations contribute to a higher probability of being acquired? We would love to start our own venture in the US and find out more about trends in the start-up world there and how will can increases our chances of being successful.

In order to find out what we should do and how we should get there we will look into different aspects of our new venture called. Firstly, we will investigate the category… Secondly, we will look at location Lastly, at time and when we should plan to reach our first milestones and secure funding rounds. In the end we will use the insights gained from this and build a prediction model for our venture

1.0.0.0.1 Notes

Notes - category: what is the most successful category? JUN, MELONICA - location: where: map: Draw a startups map, identifying the next Silicon Valley. RICK, MEHDI Idea Josi: Maybe we can also compare it to population ? Startups per population? - time PEIJUN, JOSI when do we have to reach our milestones when do we have to our first/second/third funding round as well as funding amount

=> Build a model with it, to get highest success in start-up world in the US

Overall theme & color scheme:

The goal of this report is to
- Trace the startups funding trend in recent years. - Draw a startups map, identifying the next Silicon Valley. - Utilise data modelling to select the features that might influence startups funding and outcomes. - Predict a startup’s future based on its current characteristics. - Bring out customised advise to startups according to their segmentation.

2 Data loading

startup_data <- read_csv("data/startup data.csv") 
## Parsed with column specification:
## cols(
##   .default = col_double(),
##   state_code = col_character(),
##   zip_code = col_character(),
##   id = col_character(),
##   city = col_character(),
##   `Unnamed: 6` = col_character(),
##   name = col_character(),
##   founded_at = col_character(),
##   closed_at = col_character(),
##   first_funding_at = col_character(),
##   last_funding_at = col_character(),
##   state_code.1 = col_character(),
##   category_code = col_character(),
##   object_id = col_character(),
##   status = col_character()
## )
## See spec(...) for full column specifications.
glimpse(startup_data)
## Rows: 923
## Columns: 49
## $ `Unnamed: 0`             <dbl> 1005, 204, 1001, 738, 1002, 379, 195, 875,...
## $ state_code               <chr> "CA", "CA", "CA", "CA", "CA", "CA", "CA", ...
## $ latitude                 <dbl> 42.35888, 37.23892, 32.90105, 37.32031, 37...
## $ longitude                <dbl> -71.05682, -121.97372, -117.19266, -122.05...
## $ zip_code                 <chr> "92101", "95032", "92121", "95014", "94105...
## $ id                       <chr> "c:6669", "c:16283", "c:65620", "c:42668",...
## $ city                     <chr> "San Diego", "Los Gatos", "San Diego", "Cu...
## $ `Unnamed: 6`             <chr> NA, NA, "San Diego CA 92121", "Cupertino C...
## $ name                     <chr> "Bandsintown", "TriCipher", "Plixi", "Soli...
## $ labels                   <dbl> 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, ...
## $ founded_at               <chr> "1/1/2007", "1/1/2000", "3/18/2009", "1/1/...
## $ closed_at                <chr> NA, NA, NA, NA, "10/1/2012", "2/15/2009", ...
## $ first_funding_at         <chr> "4/1/2009", "2/14/2005", "3/30/2010", "2/1...
## $ last_funding_at          <chr> "1/1/2010", "12/28/2009", "3/30/2010", "4/...
## $ age_first_funding_year   <dbl> 2.2493, 5.1260, 1.0329, 3.1315, 0.0000, 4....
## $ age_last_funding_year    <dbl> 3.0027, 9.9973, 1.0329, 5.3151, 1.6685, 4....
## $ age_first_milestone_year <dbl> 4.6685, 7.0055, 1.4575, 6.0027, 0.0384, 5....
## $ age_last_milestone_year  <dbl> 6.7041, 7.0055, 2.2055, 6.0027, 0.0384, 5....
## $ relationships            <dbl> 3, 9, 5, 5, 2, 3, 6, 25, 13, 14, 22, 8, 0,...
## $ funding_rounds           <dbl> 3, 4, 1, 3, 2, 1, 3, 3, 3, 3, 3, 5, 1, 3, ...
## $ funding_total_usd        <dbl> 375000, 40100000, 2600000, 40000000, 13000...
## $ milestones               <dbl> 3, 1, 2, 1, 1, 1, 2, 3, 4, 4, 3, 2, 0, 3, ...
## $ state_code.1             <chr> "CA", "CA", "CA", "CA", "CA", "CA", "CA", ...
## $ is_CA                    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, ...
## $ is_NY                    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, ...
## $ is_MA                    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, ...
## $ is_TX                    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_otherstate            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, ...
## $ category_code            <chr> "music", "enterprise", "web", "software", ...
## $ is_software              <dbl> 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_web                   <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, ...
## $ is_mobile                <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, ...
## $ is_enterprise            <dbl> 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_advertising           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_gamesvideo            <dbl> 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_ecommerce             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_biotech               <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_consulting            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ is_othercategory         <dbl> 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, ...
## $ object_id                <chr> "c:6669", "c:16283", "c:65620", "c:42668",...
## $ has_VC                   <dbl> 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, ...
## $ has_angel                <dbl> 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, ...
## $ has_roundA               <dbl> 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, ...
## $ has_roundB               <dbl> 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, ...
## $ has_roundC               <dbl> 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, ...
## $ has_roundD               <dbl> 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, ...
## $ avg_participants         <dbl> 1.0000, 4.7500, 4.0000, 3.3333, 1.0000, 3....
## $ is_top500                <dbl> 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, ...
## $ status                   <chr> "acquired", "acquired", "acquired", "acqui...
head(startup_data)
## # A tibble: 6 x 49
##   `Unnamed: 0` state_code latitude longitude zip_code id    city  `Unnamed: 6`
##          <dbl> <chr>         <dbl>     <dbl> <chr>    <chr> <chr> <chr>       
## 1         1005 CA             42.4     -71.1 92101    c:66~ San ~ <NA>        
## 2          204 CA             37.2    -122.  95032    c:16~ Los ~ <NA>        
## 3         1001 CA             32.9    -117.  92121    c:65~ San ~ San Diego C~
## 4          738 CA             37.3    -122.  95014    c:42~ Cupe~ Cupertino C~
## 5         1002 CA             37.8    -122.  94105    c:65~ San ~ San Francis~
## 6          379 CA             37.4    -122.  94043    c:22~ Moun~ Mountain Vi~
## # ... with 41 more variables: name <chr>, labels <dbl>, founded_at <chr>,
## #   closed_at <chr>, first_funding_at <chr>, last_funding_at <chr>,
## #   age_first_funding_year <dbl>, age_last_funding_year <dbl>,
## #   age_first_milestone_year <dbl>, age_last_milestone_year <dbl>,
## #   relationships <dbl>, funding_rounds <dbl>, funding_total_usd <dbl>,
## #   milestones <dbl>, state_code.1 <chr>, is_CA <dbl>, is_NY <dbl>,
## #   is_MA <dbl>, is_TX <dbl>, is_otherstate <dbl>, category_code <chr>,
## #   is_software <dbl>, is_web <dbl>, is_mobile <dbl>, is_enterprise <dbl>,
## #   is_advertising <dbl>, is_gamesvideo <dbl>, is_ecommerce <dbl>,
## #   is_biotech <dbl>, is_consulting <dbl>, is_othercategory <dbl>,
## #   object_id <chr>, has_VC <dbl>, has_angel <dbl>, has_roundA <dbl>,
## #   has_roundB <dbl>, has_roundC <dbl>, has_roundD <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>
describe(startup_data) 
## startup_data 
## 
##  49  Variables      923  Observations
## --------------------------------------------------------------------------------
## Unnamed: 0 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      923        1    572.3    385.4     55.1    112.2 
##      .25      .50      .75      .90      .95 
##    283.5    577.0    866.5   1028.8   1088.9 
## 
## lowest :    1    2    3    4    5, highest: 1149 1150 1151 1152 1153
## --------------------------------------------------------------------------------
## state_code 
##        n  missing distinct 
##      923        0       35 
## 
## lowest : AR AZ CA CO CT, highest: UT VA WA WI WV
## --------------------------------------------------------------------------------
## latitude 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      652        1    38.52    3.923    32.90    33.97 
##      .25      .50      .75      .90      .95 
##    37.39    37.78    40.73    42.48    45.00 
## 
## lowest : 25.75236 26.05246 26.10627 27.95185 28.03298
## highest: 47.76576 47.80218 51.43247 54.98320 59.33523
## --------------------------------------------------------------------------------
## longitude 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      651        1   -103.5    23.19  -122.42  -122.40 
##      .25      .50      .75      .90      .95 
##  -122.20  -118.37   -77.21   -73.20   -71.20 
## 
## lowest : -122.756956 -122.725662 -122.674456 -122.674195 -122.668452
## highest:  -70.923675  -70.144101   -2.664213   -1.574631   18.057121
## --------------------------------------------------------------------------------
## zip_code 
##        n  missing distinct 
##      923        0      382 
## 
## lowest : 01752-4603     01862-2000     02111-1720     10001          100011        
## highest: 98665          99202          CA 90245       CA 94105       Maryland 21045
## --------------------------------------------------------------------------------
## id 
##        n  missing distinct 
##      923        0      922 
## 
## lowest : c:10054  c:101312 c:10137  c:10153  c:10158 
## highest: c:9772   c:9782   c:9816   c:9822   c:997   
## --------------------------------------------------------------------------------
## city 
##        n  missing distinct 
##      923        0      221 
## 
## lowest : Acton       Addison     Alameda     Albuquerque Aliso Viejo
## highest: Woburn      Woodbury    Yardley     Yorba Linda Zeeland    
## --------------------------------------------------------------------------------
## Unnamed: 6 
##        n  missing distinct 
##      430      493      252 
## 
## lowest : Acton MA 1720        Addison TX 75001     Alameda CA 94501     Albuquerque NM 87102 Aliso Viejo CA 92656
## highest: Wilmington MA 1887   Woburn MA 1801       Woodbury NY 11797    Yardley PA 19067     Yorba Linda CA 92887
## --------------------------------------------------------------------------------
## name 
##        n  missing distinct 
##      923        0      922 
## 
## lowest : #waywire       1000memories   41st Parameter 5min Media     Aardvark      
## highest: ZipList        ZManda         Zong           ZoomSafer      Zymetis       
## --------------------------------------------------------------------------------
## labels 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.685      597   0.6468   0.4574 
## 
## --------------------------------------------------------------------------------
## founded_at 
##        n  missing distinct 
##      923        0      217 
## 
## lowest : 1/1/1984  1/1/1985  1/1/1992  1/1/1995  1/1/1996 
## highest: 9/19/2009 9/24/2010 9/6/2006  9/9/2009  9/9/2010 
## --------------------------------------------------------------------------------
## closed_at 
##        n  missing distinct 
##      335      588      202 
## 
## lowest : 1/1/2001  1/1/2005  1/1/2007  1/1/2008  1/1/2009 
## highest: 9/28/2011 9/4/2012  9/6/2011  9/6/2013  9/8/2013 
## --------------------------------------------------------------------------------
## first_funding_at 
##        n  missing distinct 
##      923        0      585 
## 
## lowest : 1/1/2000 1/1/2001 1/1/2002 1/1/2003 1/1/2004
## highest: 9/7/2011 9/8/2003 9/8/2005 9/9/2005 9/9/2009
## --------------------------------------------------------------------------------
## last_funding_at 
##        n  missing distinct 
##      923        0      680 
## 
## lowest : 1/1/2001 1/1/2004 1/1/2005 1/1/2006 1/1/2007
## highest: 9/7/2006 9/8/2005 9/8/2008 9/9/2008 9/9/2011
## --------------------------------------------------------------------------------
## age_first_funding_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      634        1    2.236    2.504   0.0000   0.0000 
##      .25      .50      .75      .90      .95 
##   0.5767   1.4466   3.5754   5.4241   6.5699 
## 
## lowest : -9.0466 -3.5068 -1.9863 -1.4712 -1.1836
## highest: 11.4329 16.4192 16.9863 20.8055 21.8959
## --------------------------------------------------------------------------------
## age_last_funding_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      756        1    3.931    3.208   0.2469   0.6690 
##      .25      .50      .75      .90      .95 
##   1.6699   3.5288   5.5602   7.9112   9.3616 
## 
## lowest : -9.0466 -1.9863 -1.1836 -0.9178 -0.5014
## highest: 14.9726 16.4192 16.9863 20.8055 21.8959
## --------------------------------------------------------------------------------
## age_first_milestone_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      771      152      471        1    3.055    3.149  -0.1616   0.0000 
##      .25      .50      .75      .90      .95 
##   1.0000   2.5205   4.6863   6.9589   8.2959 
## 
## lowest : -14.1699  -7.0055  -6.0466  -3.7507  -3.0000
## highest:  12.5041  13.0110  15.4986  16.6630  24.6849
## --------------------------------------------------------------------------------
## age_last_milestone_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      771      152      585        1    4.754    3.545   0.1493   1.0000 
##      .25      .50      .75      .90      .95 
##   2.4110   4.4767   6.7534   9.0055  10.4274 
## 
## lowest : -7.0055 -3.8822 -3.7507 -3.0000 -1.9151
## highest: 13.5863 14.0329 15.4986 18.3233 24.6849
## --------------------------------------------------------------------------------
## relationships 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0       41    0.995    7.711    7.073        1        1 
##      .25      .50      .75      .90      .95 
##        3        5       10       16       22 
## 
## lowest :  0  1  2  3  4, highest: 38 42 45 57 63
## --------------------------------------------------------------------------------
## funding_rounds 
##        n  missing distinct     Info     Mean      Gmd 
##      923        0        9    0.925    2.311    1.439 
## 
## lowest :  1  2  3  4  5, highest:  5  6  7  8 10
##                                                                 
## Value          1     2     3     4     5     6     7     8    10
## Frequency    317   280   167    90    40    13    13     2     1
## Proportion 0.343 0.303 0.181 0.098 0.043 0.014 0.014 0.002 0.001
## --------------------------------------------------------------------------------
## funding_total_usd 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0      505        1 25419749 36159252   186500   580000 
##      .25      .50      .75      .90      .95 
##  2725000 10000000 24725000 46700000 69540000 
## 
## lowest :      11000      12000      15000      19000      20000
## highest:  232000100  238209999  299500000  510000000 5700000000
##                                                                           
## Value      0.0e+00 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08 3.0e+08 5.0e+08
## Frequency      701     188      22       6       1       2       1       1
## Proportion   0.759   0.204   0.024   0.007   0.001   0.002   0.001   0.001
##                   
## Value      5.7e+09
## Frequency        1
## Proportion   0.001
## 
## For the frequency table, variable is rounded to the nearest 50000000
## --------------------------------------------------------------------------------
## milestones 
##        n  missing distinct     Info     Mean      Gmd 
##      923        0        8    0.949    1.842    1.452 
## 
## lowest : 0 1 2 3 4, highest: 3 4 5 6 8
##                                                           
## Value          0     1     2     3     4     5     6     8
## Frequency    152   250   246   182    62    24     6     1
## Proportion 0.165 0.271 0.267 0.197 0.067 0.026 0.007 0.001
## --------------------------------------------------------------------------------
## state_code.1 
##        n  missing distinct 
##      922        1       35 
## 
## lowest : AR AZ CA CO CT, highest: UT VA WA WI WV
## --------------------------------------------------------------------------------
## is_CA 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.748      487   0.5276    0.499 
## 
## --------------------------------------------------------------------------------
## is_NY 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.305      106   0.1148   0.2035 
## 
## --------------------------------------------------------------------------------
## is_MA 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.246       83  0.08992   0.1639 
## 
## --------------------------------------------------------------------------------
## is_TX 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2     0.13       42   0.0455  0.08696 
## 
## --------------------------------------------------------------------------------
## is_otherstate 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.517      204    0.221   0.3447 
## 
## --------------------------------------------------------------------------------
## category_code 
##        n  missing distinct 
##      923        0       35 
## 
## lowest : advertising    analytics      automotive     biotech        cleantech     
## highest: software       sports         transportation travel         web           
## --------------------------------------------------------------------------------
## is_software 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.415      153   0.1658   0.2769 
## 
## --------------------------------------------------------------------------------
## is_web 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.395      144    0.156   0.2636 
## 
## --------------------------------------------------------------------------------
## is_mobile 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.235       79  0.08559   0.1567 
## 
## --------------------------------------------------------------------------------
## is_enterprise 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.219       73  0.07909   0.1458 
## 
## --------------------------------------------------------------------------------
## is_advertising 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.188       62  0.06717   0.1255 
## 
## --------------------------------------------------------------------------------
## is_gamesvideo 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.159       52  0.05634   0.1064 
## 
## --------------------------------------------------------------------------------
## is_ecommerce 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.079       25  0.02709  0.05276 
## 
## --------------------------------------------------------------------------------
## is_biotech 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.106       34  0.03684  0.07104 
## 
## --------------------------------------------------------------------------------
## is_consulting 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2     0.01        3  0.00325 0.006486 
## 
## --------------------------------------------------------------------------------
## is_othercategory 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.656      298   0.3229   0.4377 
## 
## --------------------------------------------------------------------------------
## object_id 
##        n  missing distinct 
##      923        0      922 
## 
## lowest : c:10054  c:101312 c:10137  c:10153  c:10158 
## highest: c:9772   c:9782   c:9816   c:9822   c:997   
## --------------------------------------------------------------------------------
## has_VC 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.659      301   0.3261     0.44 
## 
## --------------------------------------------------------------------------------
## has_angel 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.569      235   0.2546     0.38 
## 
## --------------------------------------------------------------------------------
## has_roundA 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2     0.75      469   0.5081   0.5004 
## 
## --------------------------------------------------------------------------------
## has_roundB 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.715      362   0.3922   0.4773 
## 
## --------------------------------------------------------------------------------
## has_roundC 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.536      215   0.2329   0.3577 
## 
## --------------------------------------------------------------------------------
## has_roundD 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.269       92  0.09967   0.1797 
## 
## --------------------------------------------------------------------------------
## avg_participants 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      923        0       59     0.98    2.839    1.922      1.0      1.0 
##      .25      .50      .75      .90      .95 
##      1.5      2.5      3.8      5.0      6.0 
## 
## lowest :  1.0000  1.2500  1.3333  1.4000  1.5000
## highest: 10.0000 11.0000 11.5000 12.5000 16.0000
## --------------------------------------------------------------------------------
## is_top500 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      923        0        2    0.463      747   0.8093    0.309 
## 
## --------------------------------------------------------------------------------
## status 
##        n  missing distinct 
##      923        0        2 
##                             
## Value      acquired   closed
## Frequency       597      326
## Proportion    0.647    0.353
## --------------------------------------------------------------------------------
# add to new data frame to process and clean the data
startup_data_process <- startup_data

3 Data cleaning

After skimming the data to get a good overview, we will clean the data. First, we will check for missing values and duplicates.

# clean names
startup_data_process <- clean_names(startup_data_process)

3.1 Duplicates

## # A tibble: 2 x 50
##   object_id dupe_count unnamed_0 state_code latitude longitude zip_code id   
##   <chr>          <int>     <dbl> <chr>         <dbl>     <dbl> <chr>    <chr>
## 1 c:28482            2       506 CA             37.5     -122. 94538    c:28~
## 2 c:28482            2       505 CA             37.5     -122. 94538    c:28~
## # ... with 42 more variables: city <chr>, unnamed_6 <chr>, name <chr>,
## #   labels <dbl>, founded_at <chr>, closed_at <chr>, first_funding_at <chr>,
## #   last_funding_at <chr>, age_first_funding_year <dbl>,
## #   age_last_funding_year <dbl>, age_first_milestone_year <dbl>,
## #   age_last_milestone_year <dbl>, relationships <dbl>, funding_rounds <dbl>,
## #   funding_total_usd <dbl>, milestones <dbl>, state_code_1 <chr>, is_ca <dbl>,
## #   is_ny <dbl>, is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>,
## #   category_code <chr>, is_software <dbl>, is_web <dbl>, is_mobile <dbl>,
## #   is_enterprise <dbl>, is_advertising <dbl>, is_gamesvideo <dbl>,
## #   is_ecommerce <dbl>, is_biotech <dbl>, is_consulting <dbl>,
## #   is_othercategory <dbl>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>

There is one duplicate for the start-up “Redwood Systems”, which have slightly different coordinates. Perhaps, they have moved locations but since they are both in California and still have the same zip code we will just remove the row that does not have an exact address.

# removing the duplicate row
startup_data_process <- startup_data_process[ !(startup_data_process$unnamed_0 == 505), ]

# checking if there still are duplicates
dupes <- startup_data_process %>% 
  get_dupes(object_id)
## No duplicate combinations found of: object_id
dupes
## # A tibble: 0 x 50
## # ... with 50 variables: object_id <chr>, dupe_count <int>, unnamed_0 <dbl>,
## #   state_code <chr>, latitude <dbl>, longitude <dbl>, zip_code <chr>,
## #   id <chr>, city <chr>, unnamed_6 <chr>, name <chr>, labels <dbl>,
## #   founded_at <chr>, closed_at <chr>, first_funding_at <chr>,
## #   last_funding_at <chr>, age_first_funding_year <dbl>,
## #   age_last_funding_year <dbl>, age_first_milestone_year <dbl>,
## #   age_last_milestone_year <dbl>, relationships <dbl>, funding_rounds <dbl>,
## #   funding_total_usd <dbl>, milestones <dbl>, state_code_1 <chr>, is_ca <dbl>,
## #   is_ny <dbl>, is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>,
## #   category_code <chr>, is_software <dbl>, is_web <dbl>, is_mobile <dbl>,
## #   is_enterprise <dbl>, is_advertising <dbl>, is_gamesvideo <dbl>,
## #   is_ecommerce <dbl>, is_biotech <dbl>, is_consulting <dbl>,
## #   is_othercategory <dbl>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>

3.2 Missing data

After there are now more duplicates, we will start dealing with missing data.

# investigate the missing values
describe(startup_data_process)    
## startup_data_process 
## 
##  49  Variables      922  Observations
## --------------------------------------------------------------------------------
## unnamed_0 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      922        1    572.4    385.6    55.05   112.10 
##      .25      .50      .75      .90      .95 
##   283.25   577.50   866.75  1028.90  1088.95 
## 
## lowest :    1    2    3    4    5, highest: 1149 1150 1151 1152 1153
## --------------------------------------------------------------------------------
## state_code 
##        n  missing distinct 
##      922        0       35 
## 
## lowest : AR AZ CA CO CT, highest: UT VA WA WI WV
## --------------------------------------------------------------------------------
## latitude 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      651        1    38.52    3.926    32.90    33.97 
##      .25      .50      .75      .90      .95 
##    37.39    37.78    40.73    42.48    45.01 
## 
## lowest : 25.75236 26.05246 26.10627 27.95185 28.03298
## highest: 47.76576 47.80218 51.43247 54.98320 59.33523
## --------------------------------------------------------------------------------
## longitude 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      650        1   -103.5     23.2  -122.42  -122.40 
##      .25      .50      .75      .90      .95 
##  -122.20  -118.37   -77.21   -73.20   -71.20 
## 
## lowest : -122.756956 -122.725662 -122.674456 -122.674195 -122.668452
## highest:  -70.923675  -70.144101   -2.664213   -1.574631   18.057121
## --------------------------------------------------------------------------------
## zip_code 
##        n  missing distinct 
##      922        0      382 
## 
## lowest : 01752-4603     01862-2000     02111-1720     10001          100011        
## highest: 98665          99202          CA 90245       CA 94105       Maryland 21045
## --------------------------------------------------------------------------------
## id 
##        n  missing distinct 
##      922        0      922 
## 
## lowest : c:10054  c:101312 c:10137  c:10153  c:10158 
## highest: c:9772   c:9782   c:9816   c:9822   c:997   
## --------------------------------------------------------------------------------
## city 
##        n  missing distinct 
##      922        0      221 
## 
## lowest : Acton       Addison     Alameda     Albuquerque Aliso Viejo
## highest: Woburn      Woodbury    Yardley     Yorba Linda Zeeland    
## --------------------------------------------------------------------------------
## unnamed_6 
##        n  missing distinct 
##      430      492      252 
## 
## lowest : Acton MA 1720        Addison TX 75001     Alameda CA 94501     Albuquerque NM 87102 Aliso Viejo CA 92656
## highest: Wilmington MA 1887   Woburn MA 1801       Woodbury NY 11797    Yardley PA 19067     Yorba Linda CA 92887
## --------------------------------------------------------------------------------
## name 
##        n  missing distinct 
##      922        0      922 
## 
## lowest : #waywire       1000memories   41st Parameter 5min Media     Aardvark      
## highest: ZipList        ZManda         Zong           ZoomSafer      Zymetis       
## --------------------------------------------------------------------------------
## labels 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.686      596   0.6464   0.4576 
## 
## --------------------------------------------------------------------------------
## founded_at 
##        n  missing distinct 
##      922        0      217 
## 
## lowest : 1/1/1984  1/1/1985  1/1/1992  1/1/1995  1/1/1996 
## highest: 9/19/2009 9/24/2010 9/6/2006  9/9/2009  9/9/2010 
## --------------------------------------------------------------------------------
## closed_at 
##        n  missing distinct 
##      335      587      202 
## 
## lowest : 1/1/2001  1/1/2005  1/1/2007  1/1/2008  1/1/2009 
## highest: 9/28/2011 9/4/2012  9/6/2011  9/6/2013  9/8/2013 
## --------------------------------------------------------------------------------
## first_funding_at 
##        n  missing distinct 
##      922        0      585 
## 
## lowest : 1/1/2000 1/1/2001 1/1/2002 1/1/2003 1/1/2004
## highest: 9/7/2011 9/8/2003 9/8/2005 9/9/2005 9/9/2009
## --------------------------------------------------------------------------------
## last_funding_at 
##        n  missing distinct 
##      922        0      680 
## 
## lowest : 1/1/2001 1/1/2004 1/1/2005 1/1/2006 1/1/2007
## highest: 9/7/2006 9/8/2005 9/8/2008 9/9/2008 9/9/2011
## --------------------------------------------------------------------------------
## age_first_funding_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      634        1    2.237    2.506   0.0000   0.0000 
##      .25      .50      .75      .90      .95 
##   0.5746   1.4493   3.5781   5.4244   6.5712 
## 
## lowest : -9.0466 -3.5068 -1.9863 -1.4712 -1.1836
## highest: 11.4329 16.4192 16.9863 20.8055 21.8959
## --------------------------------------------------------------------------------
## age_last_funding_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      756        1    3.931     3.21   0.2467   0.6688 
##      .25      .50      .75      .90      .95 
##   1.6692   3.5206   5.5609   7.9158   9.3616 
## 
## lowest : -9.0466 -1.9863 -1.1836 -0.9178 -0.5014
## highest: 14.9726 16.4192 16.9863 20.8055 21.8959
## --------------------------------------------------------------------------------
## age_first_milestone_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      770      152      471        1    3.056    3.152  -0.1616   0.0000 
##      .25      .50      .75      .90      .95 
##   1.0000   2.5191   4.6883   6.9597   8.3085 
## 
## lowest : -14.1699  -7.0055  -6.0466  -3.7507  -3.0000
## highest:  12.5041  13.0110  15.4986  16.6630  24.6849
## --------------------------------------------------------------------------------
## age_last_milestone_year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      770      152      585        1    4.755    3.548   0.1481   1.0000 
##      .25      .50      .75      .90      .95 
##   2.3973   4.4822   6.7534   9.0055  10.4307 
## 
## lowest : -7.0055 -3.8822 -3.7507 -3.0000 -1.9151
## highest: 13.5863 14.0329 15.4986 18.3233 24.6849
## --------------------------------------------------------------------------------
## relationships 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0       41    0.995    7.704     7.07        1        1 
##      .25      .50      .75      .90      .95 
##        3        5       10       16       22 
## 
## lowest :  0  1  2  3  4, highest: 38 42 45 57 63
## --------------------------------------------------------------------------------
## funding_rounds 
##        n  missing distinct     Info     Mean      Gmd 
##      922        0        9    0.924    2.309    1.438 
## 
## lowest :  1  2  3  4  5, highest:  5  6  7  8 10
##                                                                 
## Value          1     2     3     4     5     6     7     8    10
## Frequency    317   280   167    89    40    13    13     2     1
## Proportion 0.344 0.304 0.181 0.097 0.043 0.014 0.014 0.002 0.001
## --------------------------------------------------------------------------------
## funding_total_usd 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0      505        1 25410172 36168148   185750   577500 
##      .25      .50      .75      .90      .95 
##  2712500 10000000 24652635 46750000 69570000 
## 
## lowest :      11000      12000      15000      19000      20000
## highest:  232000100  238209999  299500000  510000000 5700000000
##                                                                           
## Value      0.0e+00 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08 3.0e+08 5.0e+08
## Frequency      701     187      22       6       1       2       1       1
## Proportion   0.760   0.203   0.024   0.007   0.001   0.002   0.001   0.001
##                   
## Value      5.7e+09
## Frequency        1
## Proportion   0.001
## 
## For the frequency table, variable is rounded to the nearest 50000000
## --------------------------------------------------------------------------------
## milestones 
##        n  missing distinct     Info     Mean      Gmd 
##      922        0        8    0.949    1.842    1.453 
## 
## lowest : 0 1 2 3 4, highest: 3 4 5 6 8
##                                                           
## Value          0     1     2     3     4     5     6     8
## Frequency    152   250   245   182    62    24     6     1
## Proportion 0.165 0.271 0.266 0.197 0.067 0.026 0.007 0.001
## --------------------------------------------------------------------------------
## state_code_1 
##        n  missing distinct 
##      921        1       35 
## 
## lowest : AR AZ CA CO CT, highest: UT VA WA WI WV
## --------------------------------------------------------------------------------
## is_ca 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.748      486   0.5271   0.4991 
## 
## --------------------------------------------------------------------------------
## is_ny 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.305      106    0.115   0.2037 
## 
## --------------------------------------------------------------------------------
## is_ma 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.246       83  0.09002    0.164 
## 
## --------------------------------------------------------------------------------
## is_tx 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2     0.13       42  0.04555  0.08705 
## 
## --------------------------------------------------------------------------------
## is_otherstate 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.517      204   0.2213    0.345 
## 
## --------------------------------------------------------------------------------
## category_code 
##        n  missing distinct 
##      922        0       35 
## 
## lowest : advertising    analytics      automotive     biotech        cleantech     
## highest: software       sports         transportation travel         web           
## --------------------------------------------------------------------------------
## is_software 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.415      153   0.1659   0.2771 
## 
## --------------------------------------------------------------------------------
## is_web 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.395      144   0.1562   0.2639 
## 
## --------------------------------------------------------------------------------
## is_mobile 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.235       79  0.08568   0.1569 
## 
## --------------------------------------------------------------------------------
## is_enterprise 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.219       73  0.07918    0.146 
## 
## --------------------------------------------------------------------------------
## is_advertising 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.188       62  0.06725   0.1256 
## 
## --------------------------------------------------------------------------------
## is_gamesvideo 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2     0.16       52   0.0564   0.1066 
## 
## --------------------------------------------------------------------------------
## is_ecommerce 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.079       25  0.02711  0.05282 
## 
## --------------------------------------------------------------------------------
## is_biotech 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.107       34  0.03688  0.07111 
## 
## --------------------------------------------------------------------------------
## is_consulting 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2     0.01        3 0.003254 0.006493 
## 
## --------------------------------------------------------------------------------
## is_othercategory 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.655      297   0.3221   0.4372 
## 
## --------------------------------------------------------------------------------
## object_id 
##        n  missing distinct 
##      922        0      922 
## 
## lowest : c:10054  c:101312 c:10137  c:10153  c:10158 
## highest: c:9772   c:9782   c:9816   c:9822   c:997   
## --------------------------------------------------------------------------------
## has_vc 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.659      300   0.3254   0.4395 
## 
## --------------------------------------------------------------------------------
## has_angel 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2     0.57      235   0.2549   0.3802 
## 
## --------------------------------------------------------------------------------
## has_round_a 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2     0.75      468   0.5076   0.5004 
## 
## --------------------------------------------------------------------------------
## has_round_b 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.715      361   0.3915    0.477 
## 
## --------------------------------------------------------------------------------
## has_round_c 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.535      214   0.2321   0.3569 
## 
## --------------------------------------------------------------------------------
## has_round_d 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.269       92  0.09978   0.1798 
## 
## --------------------------------------------------------------------------------
## avg_participants 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##      922        0       59     0.98    2.839    1.923      1.0      1.0 
##      .25      .50      .75      .90      .95 
##      1.5      2.5      3.8      5.0      6.0 
## 
## lowest :  1.0000  1.2500  1.3333  1.4000  1.5000
## highest: 10.0000 11.0000 11.5000 12.5000 16.0000
## --------------------------------------------------------------------------------
## is_top500 
##        n  missing distinct     Info      Sum     Mean      Gmd 
##      922        0        2    0.463      746   0.8091   0.3092 
## 
## --------------------------------------------------------------------------------
## status 
##        n  missing distinct 
##      922        0        2 
##                             
## Value      acquired   closed
## Frequency       596      326
## Proportion    0.646    0.354
## --------------------------------------------------------------------------------
#  use the md.pattern function from MICE package
md.pattern(startup_data_process, rotate.names = T)

##     unnamed_0 state_code latitude longitude zip_code id city name labels
## 120         1          1        1         1        1  1    1    1      1
## 219         1          1        1         1        1  1    1    1      1
## 109         1          1        1         1        1  1    1    1      1
## 321         1          1        1         1        1  1    1    1      1
## 67          1          1        1         1        1  1    1    1      1
## 24          1          1        1         1        1  1    1    1      1
## 38          1          1        1         1        1  1    1    1      1
## 23          1          1        1         1        1  1    1    1      1
## 1           1          1        1         1        1  1    1    1      1
##             0          0        0         0        0  0    0    0      0
##     founded_at first_funding_at last_funding_at age_first_funding_year
## 120          1                1               1                      1
## 219          1                1               1                      1
## 109          1                1               1                      1
## 321          1                1               1                      1
## 67           1                1               1                      1
## 24           1                1               1                      1
## 38           1                1               1                      1
## 23           1                1               1                      1
## 1            1                1               1                      1
##              0                0               0                      0
##     age_last_funding_year relationships funding_rounds funding_total_usd
## 120                     1             1              1                 1
## 219                     1             1              1                 1
## 109                     1             1              1                 1
## 321                     1             1              1                 1
## 67                      1             1              1                 1
## 24                      1             1              1                 1
## 38                      1             1              1                 1
## 23                      1             1              1                 1
## 1                       1             1              1                 1
##                         0             0              0                 0
##     milestones is_ca is_ny is_ma is_tx is_otherstate category_code is_software
## 120          1     1     1     1     1             1             1           1
## 219          1     1     1     1     1             1             1           1
## 109          1     1     1     1     1             1             1           1
## 321          1     1     1     1     1             1             1           1
## 67           1     1     1     1     1             1             1           1
## 24           1     1     1     1     1             1             1           1
## 38           1     1     1     1     1             1             1           1
## 23           1     1     1     1     1             1             1           1
## 1            1     1     1     1     1             1             1           1
##              0     0     0     0     0             0             0           0
##     is_web is_mobile is_enterprise is_advertising is_gamesvideo is_ecommerce
## 120      1         1             1              1             1            1
## 219      1         1             1              1             1            1
## 109      1         1             1              1             1            1
## 321      1         1             1              1             1            1
## 67       1         1             1              1             1            1
## 24       1         1             1              1             1            1
## 38       1         1             1              1             1            1
## 23       1         1             1              1             1            1
## 1        1         1             1              1             1            1
##          0         0             0              0             0            0
##     is_biotech is_consulting is_othercategory object_id has_vc has_angel
## 120          1             1                1         1      1         1
## 219          1             1                1         1      1         1
## 109          1             1                1         1      1         1
## 321          1             1                1         1      1         1
## 67           1             1                1         1      1         1
## 24           1             1                1         1      1         1
## 38           1             1                1         1      1         1
## 23           1             1                1         1      1         1
## 1            1             1                1         1      1         1
##              0             0                0         0      0         0
##     has_round_a has_round_b has_round_c has_round_d avg_participants is_top500
## 120           1           1           1           1                1         1
## 219           1           1           1           1                1         1
## 109           1           1           1           1                1         1
## 321           1           1           1           1                1         1
## 67            1           1           1           1                1         1
## 24            1           1           1           1                1         1
## 38            1           1           1           1                1         1
## 23            1           1           1           1                1         1
## 1             1           1           1           1                1         1
##               0           0           0           0                0         0
##     status state_code_1 age_first_milestone_year age_last_milestone_year
## 120      1            1                        1                       1
## 219      1            1                        1                       1
## 109      1            1                        1                       1
## 321      1            1                        1                       1
## 67       1            1                        0                       0
## 24       1            1                        0                       0
## 38       1            1                        0                       0
## 23       1            1                        0                       0
## 1        1            0                        1                       1
##          0            1                      152                     152
##     unnamed_6 closed_at     
## 120         1         1    0
## 219         1         0    1
## 109         0         1    1
## 321         0         0    2
## 67          1         1    2
## 24          1         0    3
## 38          0         1    3
## 23          0         0    4
## 1           0         1    2
##           492       587 1384

There are some missing values for - Unnamed_6: this is a more detailed address, we will delete this column - closed_at - age_first_milestone_year - age_last_milestone_year - state_code.1

# delete unnamed_6
startup_data_process <- startup_data_process %>%
  select(-unnamed_6)

# cross-check if closed_at only occurs for start-ups that are not acquired
check_closedat <- startup_data_process %>%
  filter(is.na(closed_at) & status == "closed")
# this is the case, so we will leave na here

# cross-check if milestone values are missing if there have not been any milestones
check_milestones <- startup_data_process %>%
  filter((is.na(age_first_milestone_year) & milestones != 0) | # or
           (is.na(age_last_milestone_year) & milestones != 0))
# this is the case, so we will leave na here

# replace the missing state, which is CA (after research)
startup_data_process$state_code_1 <- ifelse(is.na(startup_data_process$state_code_1), 'CA', startup_data_process$state_code_1)

3.3 Data types

Next, we will look at the data types. The dates still have to be put into the correct data type

Other ones as well?

# converting the dates into data format
startup_data_process <- startup_data_process %>%
  mutate(founded_at = mdy(founded_at), 
         closed_at = mdy(closed_at), 
         first_funding_at = mdy(first_funding_at), 
         last_funding_at = mdy(last_funding_at))

3.4 Create new variables

create age in year create year founded (extract from day) create area variable (West coast, East Cost etc) create

# create year founded  
startup_data_process <- startup_data_process %>% 
  mutate(year_founded = year(founded_at))
# make a new category variables -> maybe use top 6 and rest into others 
startup_data_process <- startup_data_process %>% 
  mutate(category1 = ifelse ((category_code != 'software' & 
                                category_code!= 'web' & 
                                category_code != 'mobile' & 
                                category_code != 'enterprise' & 
                                category_code != 'advertising' & 
                                category_code != 'games_video' & 
                                category_code != 'ecommerce' & 
                                category_code != 'biotech' & 
                                category_code != 'consulting'), 
                             'other_category', 
                             startup_data_process$category_code))
startup_data_process <- startup_data_process %>% 
  mutate(category2 = ifelse ((category_code != 'software' & 
                                category_code!= 'web' & 
                                category_code != 'mobile' & 
                                category_code != 'advertising' & 
                                category_code != 'games_video' & 
                                category_code != 'ecommerce' ), 
                             'other_category', 
                             startup_data_process$category_code))

After the data cleaning we will assign it back to the original data set and then start our exploratory data analysis.

# assign the cleaned data back to the original data set so that we can work
startup_data <- startup_data_process

4 Exploratory data analaysis

4.1 Check numerical variables

  1. Check max, min, and distribution of numerical values.
  • some ages are negative -> what do we do with these? (either make 0 or delete) -> most differences are very small make those with less than a month 0, others delete

4.1.1 Funding Amount

First, we look into the distribution of the funding amount. It is highly right-skewed, which is why we take the log

startup_data %>% 
  ggplot(aes(
    x = funding_total_usd
  )) +
    geom_boxplot()+
  coord_flip()

startup_data %>% 
  ggplot(aes(
    x = funding_total_usd
  )) +
    geom_histogram() 
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

startup_data %>% 
  ggplot(aes(
    x = log(funding_total_usd)
  )) +
    geom_boxplot() +
    coord_flip()

startup_data %>% 
  ggplot(aes(
    x = log(funding_total_usd)
  )) +
    geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

startup_data %>% 
  arrange(desc(funding_total_usd)) %>% 
  head(10)
## # A tibble: 10 x 51
##    unnamed_0 state_code latitude longitude zip_code id    city  name  labels
##        <dbl> <chr>         <dbl>     <dbl> <chr>    <chr> <chr> <chr>  <dbl>
##  1        86 WA             30.6     -87.0 98033    c:13~ Kirk~ Clea~      1
##  2       863 CO             40.4    -105.  80538    c:51~ Love~ Abou~      0
##  3       642 TX             30.3     -97.7 78701    c:36~ Aust~ Reta~      1
##  4        59 IN             39.8     -86.2 46204    c:12~ Indi~ Exac~      1
##  5       440 CA             37.5    -122.  94063    c:25~ Redw~ Pear~      1
##  6        54 CA             37.4    -122.  95112    c:12~ San ~ SolF~      0
##  7       433 NC             35.7     -79.2 27312    c:25~ Pitt~ Biol~      0
##  8       297 CA             37.4    -122.  95131    c:18~ San ~ Cyph~      0
##  9         6 CA             37.8    -122.  94103    c:10~ San ~ Yamm~      1
## 10       474 MA             42.5     -71.3 1821     c:27~ Bill~ Lumi~      1
## # ... with 42 more variables: founded_at <date>, closed_at <date>,
## #   first_funding_at <date>, last_funding_at <date>,
## #   age_first_funding_year <dbl>, age_last_funding_year <dbl>,
## #   age_first_milestone_year <dbl>, age_last_milestone_year <dbl>,
## #   relationships <dbl>, funding_rounds <dbl>, funding_total_usd <dbl>,
## #   milestones <dbl>, state_code_1 <chr>, is_ca <dbl>, is_ny <dbl>,
## #   is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>, category_code <chr>,
## #   is_software <dbl>, is_web <dbl>, is_mobile <dbl>, is_enterprise <dbl>,
## #   is_advertising <dbl>, is_gamesvideo <dbl>, is_ecommerce <dbl>,
## #   is_biotech <dbl>, is_consulting <dbl>, is_othercategory <dbl>,
## #   object_id <chr>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>, year_founded <dbl>,
## #   category1 <chr>, category2 <chr>
startup_data_process %>% 
  arrange(funding_total_usd) %>% 
  head(10)
## # A tibble: 10 x 51
##    unnamed_0 state_code latitude longitude zip_code id    city  name  labels
##        <dbl> <chr>         <dbl>     <dbl> <chr>    <chr> <chr> <chr>  <dbl>
##  1      1075 NY             43.0     -78.9 14217    c:79~ Kenm~ Trus~      0
##  2       963 WA             47.6    -122.  98109    c:60~ Seat~ Worl~      0
##  3       159 TN             35.1     -90.1 38103-4~ c:15~ Memp~ Frie~      0
##  4       131 OH             41.7     -83.5 43607    c:14~ Tole~ Clas~      0
##  5       160 GA             34.0     -84.0 30043    c:15~ Lawr~ Nala~      0
##  6       985 CA             37.8    -122.  94609    c:63~ Oakl~ Slip~      0
##  7       392 VA             38.9     -77.1 22201    c:23~ Arli~ Soci~      0
##  8       876 TX             30.3     -97.7 78701    c:51~ Aust~ Hurr~      0
##  9       455 MI             42.8     -86.0 49464    c:26~ Zeel~ Reve~      0
## 10       144 OH             39.1     -84.5 45202    c:15~ Cinc~ Styl~      0
## # ... with 42 more variables: founded_at <date>, closed_at <date>,
## #   first_funding_at <date>, last_funding_at <date>,
## #   age_first_funding_year <dbl>, age_last_funding_year <dbl>,
## #   age_first_milestone_year <dbl>, age_last_milestone_year <dbl>,
## #   relationships <dbl>, funding_rounds <dbl>, funding_total_usd <dbl>,
## #   milestones <dbl>, state_code_1 <chr>, is_ca <dbl>, is_ny <dbl>,
## #   is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>, category_code <chr>,
## #   is_software <dbl>, is_web <dbl>, is_mobile <dbl>, is_enterprise <dbl>,
## #   is_advertising <dbl>, is_gamesvideo <dbl>, is_ecommerce <dbl>,
## #   is_biotech <dbl>, is_consulting <dbl>, is_othercategory <dbl>,
## #   object_id <chr>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>, year_founded <dbl>,
## #   category1 <chr>, category2 <chr>

4.1.2 Funding rounds

# startups according to funding round
startup_data %>% 
  group_by(funding_rounds) %>% 
  summarise(count_funding=n())
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 9 x 2
##   funding_rounds count_funding
##            <dbl>         <int>
## 1              1           317
## 2              2           280
## 3              3           167
## 4              4            89
## 5              5            40
## 6              6            13
## 7              7            13
## 8              8             2
## 9             10             1

4.1.3 Age (funding & milestones)

startup_data %>% 
  ggplot(aes(
    x = age_first_funding_year,
    colour = status
  )) +
  geom_density()

startup_data %>% 
  ggplot(aes(
    x = age_last_funding_year,
    colour = status
  )) +
  geom_density()

startup_data %>% 
  ggplot(aes(
    x = age_first_milestone_year,
    colour = status
  )) +
  geom_density()
## Warning: Removed 152 rows containing non-finite values (stat_density).

startup_data %>% 
  ggplot(aes(
    x = age_last_milestone_year,
    colour = status
  )) +
  geom_density()
## Warning: Removed 152 rows containing non-finite values (stat_density).

startup_data %>% 
  ggplot(aes(
    x = milestones,
    fill = status
  )) +
  geom_bar()

startup_data %>% 
  ggplot(aes(
    x = funding_rounds,
    fill = status
  )) +
  geom_bar()

4.2 Check categorical variables

-> Names and distributions of categorical values. For the categorical variables, we looked into the sectors:

5 Categories

startup_data %>%
  group_by(category_code) %>% 
  summarise(count_category = n()) %>%
  arrange(desc(count_category))
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 35 x 2
##    category_code   count_category
##    <chr>                    <int>
##  1 software                   153
##  2 web                        144
##  3 mobile                      79
##  4 enterprise                  73
##  5 advertising                 62
##  6 games_video                 52
##  7 semiconductor               35
##  8 biotech                     34
##  9 network_hosting             34
## 10 hardware                    27
## # ... with 25 more rows
# we have 35 categories of startups  with the highest number of startups in software

startup_data %>%
  group_by(category_code) %>% 
  summarise(count = n()) %>% 
  ggplot(aes(
    x = reorder(category_code, count),
    y = count
  )) +
  geom_col() +
  coord_flip() +
  labs(
    x = "startup category",
    y = "number of startups"
  )
## `summarise()` ungrouping output (override with `.groups` argument)

startup_data %>% 
  group_by(category_code, status) %>% 
  summarise(count = n()) %>% 
  ggplot(aes(
    x = reorder(category_code, count),
    y = count,
    fill = reorder(status, desc(status))
  )) +
  geom_col() +
  coord_flip() +
  scale_fill_manual(values = c("#FF3333", "#00CC66")) +
  labs(fill = "start up status",
       x = "category")
## `summarise()` regrouping output by 'category_code' (override with `.groups` argument)

5.0.1 States and Location

Next, we will look at the locations of the start-ups. Start-ups are located in 35 different states, with most of them being in California

# look at the start-ups per state
startup_data %>% 
  group_by(state_code_1) %>%
  summarise(count_state = n()) %>%
  arrange(desc(count_state))
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 35 x 2
##    state_code_1 count_state
##    <chr>              <int>
##  1 CA                   487
##  2 NY                   106
##  3 MA                    83
##  4 TX                    42
##  5 WA                    42
##  6 CO                    19
##  7 IL                    18
##  8 PA                    17
##  9 VA                    13
## 10 GA                    11
## # ... with 25 more rows
# we have 35 states with startups with highest number of startups in California
library(sf)
remotes::install_github("UrbanInstitute/urbnmapr")
## Skipping install of 'urbnmapr' from a github remote, the SHA1 (ef9f4488) has not changed since last install.
##   Use `force = TRUE` to force installation
library(urbnmapr)

counties_sf <- get_urbn_map("counties", sf = TRUE)

counties_sf
## Simple feature collection with 3142 features and 6 fields
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: -2600000 ymin: -2363000 xmax: 2516374 ymax: 732352.2
## projected CRS:  US National Atlas Equal Area
## First 10 features:
##    county_fips state_abbv state_fips       county_name fips_class
## 1        04015         AZ         04     Mohave County         H1
## 2        12035         FL         12    Flagler County         H1
## 3        20129         KS         20     Morton County         H1
## 4        28093         MS         28   Marshall County         H1
## 5        29510         MO         29    St. Louis city         C7
## 6        35031         NM         35   McKinley County         H1
## 7        37187         NC         37 Washington County         H1
## 8        38013         ND         38      Burke County         H1
## 9        51700         VA         51 Newport News city         C7
## 10       20109         KS         20      Logan County         H1
##        state_name                       geometry
## 1         Arizona MULTIPOLYGON (((-1321573 -8...
## 2         Florida MULTIPOLYGON (((1785548 -15...
## 3          Kansas MULTIPOLYGON (((-181692.7 -...
## 4     Mississippi MULTIPOLYGON (((936765 -105...
## 5        Missouri MULTIPOLYGON (((840327.3 -6...
## 6      New Mexico MULTIPOLYGON (((-819326.8 -...
## 7  North Carolina MULTIPOLYGON (((2064587 -74...
## 8    North Dakota MULTIPOLYGON (((-214456.6 4...
## 9        Virginia MULTIPOLYGON (((2043776 -58...
## 10         Kansas MULTIPOLYGON (((-127652.9 -...
class(counties_sf)
## [1] "sf"         "data.frame"
counties_sf$geometry
## Geometry set for 3142 features 
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: -2600000 ymin: -2363000 xmax: 2516374 ymax: 732352.2
## projected CRS:  US National Atlas Equal Area
## First 5 geometries:
## MULTIPOLYGON (((-1321573 -873787.5, -1321334 -8...
## MULTIPOLYGON (((1785548 -1513342, 1804407 -1508...
## MULTIPOLYGON (((-181692.7 -883882.3, -181677.3 ...
## MULTIPOLYGON (((936765 -1054120, 944016.3 -1053...
## MULTIPOLYGON (((840327.3 -662360, 841064.5 -656...
counties_sf <- counties_sf %>% 
st_transform(4326)

counties_sf %>% 
  ggplot(aes()) +
  geom_sf(fill = "grey70", colour = "#ffffff") +
  geom_point(data = startup_data, aes(
    x = longitude,
    y = latitude
  ))

startup_data %>% 
  filter(longitude > -20)
## # A tibble: 4 x 51
##   unnamed_0 state_code latitude longitude zip_code id    city  name  labels
##       <dbl> <chr>         <dbl>     <dbl> <chr>    <chr> <chr> <chr>  <dbl>
## 1       542 RI             51.4     -2.66 2906     c:30~ Prov~ DiJi~      1
## 2      1016 RI             51.4     -2.66 2903     c:69~ Prov~ Trac~      1
## 3       314 CT             55.0     -1.57 6103     c:18~ Hart~ MOLI       0
## 4       290 CA             59.3     18.1  95054    c:17~ Sant~ Xele~      1
## # ... with 42 more variables: founded_at <date>, closed_at <date>,
## #   first_funding_at <date>, last_funding_at <date>,
## #   age_first_funding_year <dbl>, age_last_funding_year <dbl>,
## #   age_first_milestone_year <dbl>, age_last_milestone_year <dbl>,
## #   relationships <dbl>, funding_rounds <dbl>, funding_total_usd <dbl>,
## #   milestones <dbl>, state_code_1 <chr>, is_ca <dbl>, is_ny <dbl>,
## #   is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>, category_code <chr>,
## #   is_software <dbl>, is_web <dbl>, is_mobile <dbl>, is_enterprise <dbl>,
## #   is_advertising <dbl>, is_gamesvideo <dbl>, is_ecommerce <dbl>,
## #   is_biotech <dbl>, is_consulting <dbl>, is_othercategory <dbl>,
## #   object_id <chr>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>, year_founded <dbl>,
## #   category1 <chr>, category2 <chr>
num_by_state <- startup_data %>% 
  group_by(state_code) %>% 
  summarise(count = n())
## `summarise()` ungrouping output (override with `.groups` argument)
counties_sf_heat <- counties_sf %>% 
  left_join(num_by_state, by = c("state_abbv" = "state_code"))

counties_sf_heat %>% 
  ggplot(aes()) +
  geom_sf(aes(fill = count)) +
  scale_fill_gradient(low = "blue", high = "#98ff98")

## # A tibble: 6 x 51
##   unnamed_0 state_code latitude longitude zip_code id    city  name  labels
##       <dbl> <chr>         <dbl>     <dbl> <chr>    <chr> <chr> <chr>  <dbl>
## 1      1005 CA             42.4     -71.1 92101    c:66~ San ~ Band~      1
## 2       204 CA             37.2    -122.  95032    c:16~ Los ~ TriC~      1
## 3      1001 CA             32.9    -117.  92121    c:65~ San ~ Plixi      1
## 4       738 CA             37.3    -122.  95014    c:42~ Cupe~ Soli~      1
## 5      1002 CA             37.8    -122.  94105    c:65~ San ~ Inha~      0
## 6       379 CA             37.4    -122.  94043    c:22~ Moun~ Mati~      0
## # ... with 42 more variables: founded_at <date>, closed_at <date>,
## #   first_funding_at <date>, last_funding_at <date>,
## #   age_first_funding_year <dbl>, age_last_funding_year <dbl>,
## #   age_first_milestone_year <dbl>, age_last_milestone_year <dbl>,
## #   relationships <dbl>, funding_rounds <dbl>, funding_total_usd <dbl>,
## #   milestones <dbl>, state_code_1 <chr>, is_ca <dbl>, is_ny <dbl>,
## #   is_ma <dbl>, is_tx <dbl>, is_otherstate <dbl>, category_code <chr>,
## #   is_software <dbl>, is_web <dbl>, is_mobile <dbl>, is_enterprise <dbl>,
## #   is_advertising <dbl>, is_gamesvideo <dbl>, is_ecommerce <dbl>,
## #   is_biotech <dbl>, is_consulting <dbl>, is_othercategory <dbl>,
## #   object_id <chr>, has_vc <dbl>, has_angel <dbl>, has_round_a <dbl>,
## #   has_round_b <dbl>, has_round_c <dbl>, has_round_d <dbl>,
## #   avg_participants <dbl>, is_top500 <dbl>, status <chr>, year_founded <dbl>,
## #   category1 <chr>, category2 <chr>
## Loading required package: ggformula
## Loading required package: ggstance
## 
## Attaching package: 'ggstance'
## The following objects are masked from 'package:ggplot2':
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# Visualisations

5.1 Category -> Melonica, Jun

Which categories are most successful / get most funding? or similar

Josi: I already played with this, maybe you can use it: Which industry receives the most total funding?

funding_total <- startup_data %>%
  group_by(category1) %>%
  summarise(total_funding = (sum(funding_total_usd))/1000000) 
## `summarise()` ungrouping output (override with `.groups` argument)
funding_total_plot <- funding_total %>% 
  ggplot(aes(x = total_funding, y = reorder(category1, total_funding), fill = category1)) +
  geom_bar(stat="identity")

funding_total_plot

# funding in millions

Which industry receives the most funding on average?

funding_average <- startup_data %>%
  group_by(category1) %>%
  summarise(average_funding = (mean(funding_total_usd))/1000000) 
## `summarise()` ungrouping output (override with `.groups` argument)
funding_average_plot <- funding_average %>% 
  ggplot(aes(x = average_funding, y = reorder(category1, average_funding), fill = category1)) +
  geom_bar(stat="identity")

funding_average_plot

# funding in millions

5.2 Location -> Rick, Mehdi

make startups map, identifying the next Silicon Valley. maybe look at funding per state / success rate per state startups per population

5.3 Age: When should we aim to reach milestones and funding rounds?

Lastly, we want to get an idea of when we should aim to complete milestones as well as funding rounds.

Overall, we try to answer the following two questions: - When do we have to reach our first (and last) milestones? - When do we have to reach our first (and last) funding round?

startup_data <- startup_data %>%
  filter(age_first_milestone_year>(-(6/12)))
startup_data
unnamed_0state_codelatitudelongitudezip_codeidcitynamelabelsfounded_atclosed_atfirst_funding_atlast_funding_atage_first_funding_yearage_last_funding_yearage_first_milestone_yearage_last_milestone_yearrelationshipsfunding_roundsfunding_total_usdmilestonesstate_code_1is_cais_nyis_mais_txis_otherstatecategory_codeis_softwareis_webis_mobileis_enterpriseis_advertisingis_gamesvideois_ecommerceis_biotechis_consultingis_othercategoryobject_idhas_vchas_angelhas_round_ahas_round_bhas_round_chas_round_davg_participantsis_top500statusyear_foundedcategory1category2
1e+03       CA42.4-71.1 92101c:6669San DiegoBandsintown12007-01-012009-04-012010-01-012.25  3     4.67  6.7   333.75e+053CA10000music0000000001c:66690100001   0acquired2.01e+03other_categoryother_category
204       CA37.2-122   95032c:16283Los GatosTriCipher12000-01-012005-02-142009-12-285.13  10     7.01  7.01  944.01e+071CA10000enterprise0001000000c:162831001114.751acquired2e+03       enterpriseother_category
1e+03       CA32.9-117   92121c:65620San DiegoPlixi12009-03-182010-03-302010-03-301.03  1.03  1.46  2.21  512.6e+06 2CA10000web0100000000c:656200010004   1acquired2.01e+03webweb
738       CA37.3-122   95014c:42668CupertinoSolidcore Systems12002-01-012005-02-172007-04-253.13  5.32  6     6     534e+07       1CA10000software1000000000c:426680001113.331acquired2e+03       softwaresoftware
1e+03       CA37.8-122   94105c:65806San FranciscoInhale Digital02010-08-012012-10-012010-08-012012-04-010     1.67  0.03840.0384221.3e+06 1CA10000games_video0000010000c:658061100001   1closed2.01e+03games_videogames_video
379       CA37.4-122   94043c:22898Mountain ViewMatisse Networks02002-01-012009-02-152006-07-182006-07-184.55  4.55  5     5     317.5e+06 1CA10000network_hosting0000000001c:228980001003   1closed2e+03       other_categoryother_category
195       CA37.4-122   94041c:16191Mountain ViewRingCube Technologies12005-01-012006-09-212010-03-181.72  5.21  3     6.61  632.6e+07 2CA10000software1000000000c:161911011001.671acquired2e+03       softwaresoftware
875       CA38.1-123   94901c:5192San RafaelClairMail12004-01-012005-08-242010-10-041.65  6.76  5.61  7.36  2533.41e+073CA10000finance0000000001c:51920011013.5 1acquired2e+03       other_categoryother_category
16       MA42.7-73.2 1267c:1043WilliamstownVoodooVox12002-01-012005-08-022013-02-083.59  11.1   8.01  9.99  1339.65e+064MA00100mobile0010000000c:10431010014   1acquired2e+03       mobilemobile
846       CA37.4-122   94306c:498Palo AltoDoostang12005-06-012007-02-012010-02-051.67  4.68  2.92  6.12  1435.75e+064CA10000web0100000000c:4981110001   1acquired2e+03       webweb
685       CA37.4-122   94025c:3949Menlo ParkZong12000-11-152005-07-012010-04-264.63  9.45  10.1   10.6   2232.75e+073CA10000mobile0010000000c:39490011001   1acquired2e+03       mobilemobile
137       NY40.7-74   11201c:1491Brooklyndrop.io12007-11-262007-12-032010-05-030.01922.44  0.794 4.38  1539.95e+063NY01000education0000000001c:14910011102.331acquired2.01e+03other_categoryother_category
162       CO39.7-105   80202c:15645DenverStratavia12001-01-012005-08-312009-12-294.67  9     8.84  8.84  1251.07e+071CO00001software1000000000c:156450011002.5 1acquired2e+03       softwaresoftware
235       CA37.4-122   94022c:16770Los AltosQSecure02003-01-012012-09-222005-08-022009-10-052.59  6.76  5.5   5.5   854.9e+07 1CA10000security0000000001c:167701011113.5 1closed2e+03       other_categoryother_category
25       CA37.6-122   94010c:107BurlingameMeeVee12000-07-012005-02-012007-09-014.59  7.17  -0.499 12.7   742.5e+07 3CA10000games_video0000010000c:1070011113.5 1acquired2e+03       games_videogames_video
858       NY40.7-74   10004c:50727New YorkSinglePlatform12010-01-012010-09-292011-08-010.743 1.58  1.28  3     1034.58e+063NY01000web0100000000c:507270110005   1acquired2.01e+03webweb
454       CA37.4-122   94301c:26368Palo AltoBling Nation02007-01-012011-09-102009-07-022009-10-302.5   2.83  3.09  3.49  1322.8e+07 3CA10000enterprise0001000000c:263680011001   1closed2.01e+03enterpriseother_category
369       TX30.2-97.8 78735c:22291AustinMetreos Corporation12001-01-012003-03-202004-10-142.21  3.79  4.09  9.5   824.36e+063TX00010software1000000000c:222910110001.5 0acquired2e+03       softwaresoftware
289       WA47.6-122   98122c:17857SeattleHidden City Games02004-01-012011-09-282007-10-312007-10-313.83  3.83  3.75  3.75  311.5e+07 1WA00001other0000000001c:178570001002   1closed2e+03       other_categoryother_category
177       CA37.4-122   94306c:15888Palo AltoNeopolitan Networks02002-01-012008-07-252007-06-282007-06-285.49  5.49  0     0     113.17e+061CA10000web0100000000c:158880010002   0closed2e+03       webweb
26       CA37.8-122   94103c:10751San FranciscoPixelpipe02008-01-012013-08-022007-01-012011-04-25-1     3.32  3.7   5.66  422.3e+06 3CA10000mobile0010000000c:107510110002   0closed2.01e+03mobilemobile
797       IL41.9-87.6 60601c:45525ChicagoBridgePort Networks12002-01-012006-11-032006-11-034.84  4.84  1     1     311.3e+07 1IL00001software1000000000c:455250000104   1acquired2e+03       softwaresoftware
572       CA37.4-122   94303c:3193Palo AltoScalent Systems12003-01-012007-01-222007-01-224.06  4.06  3     3     711.5e+07 1CA10000public_relations0000000001c:31930000104   1acquired2e+03       other_categoryother_category
503       CA37.9-122   94704c:28456BerkeleyIQ Engines12008-06-012012-06-252012-06-254.07  4.07  3.42  5.23  213.8e+06 3CA10000photo_video0000000001c:284560001002   1acquired2.01e+03other_categoryother_category
642       TX30.3-97.7 78701c:36920AustinRetailMeNot, Inc.12007-05-012009-11-012011-11-102.51  4.53  4.93  5.68  3753e+08       2TX00010web0100000000c:369201010101.751acquired2.01e+03webweb
625       CA33.7-118   92705c:35712Santa AnaMophie12005-05-242006-08-012006-08-011.19  1.19  2.19  7.78  511e+06       3CA10000hardware0000000001c:357121000002   1acquired2e+03       other_categoryother_category
355       CA37.4-122   94035c:21492Moffett FieldAirship Ventures02007-01-012012-11-142008-05-092009-03-011.35  2.16  4.52  4.52  321.05e+071CA10000other0000000001c:214920011002   1closed2.01e+03other_categoryother_category
510       WA47.6-122   98119c:28768SeattleLockdown Networks12001-01-012005-02-252006-03-024.15  5.17  3     3     628.6e+06 1WA00001public_relations0000000001c:287681001001.5 1acquired2e+03       other_categoryother_category
145       CA37.8-122   94105c:150658San FranciscoKarma12011-01-012011-01-012011-11-140     0.869 0.414 2.17  322.3e+06 2CA10000mobile0010000000c:1506581000005   1acquired2.01e+03mobilemobile
785       NY40.7-74   10011c:45111New YorkEntertainment Media Works02004-07-012008-10-012007-02-262007-02-262.66  2.66  0     0     114e+06       1NY01000software1000000000c:451110001001   1closed2e+03       softwaresoftware
562       CA37.8-122   94111c:3178San FranciscoElastra02007-01-012011-01-282007-08-152008-08-050.619 1.59  1     4.33  821.46e+073CA10000software1000000000c:31780011002   1closed2.01e+03softwaresoftware
378       CA37.8-122   94107c:22856San FranciscoFotomoto12008-10-012008-12-012011-05-260.167 2.65  0.608 4.75  1031.82e+063CA10000ecommerce0000001000c:228560110002.331acquired2.01e+03ecommerceecommerce
63       NY40.8-74   10010c:1224New YorkPeer3912006-03-012006-03-012012-01-240     5.9   3.84  7.14  1872.99e+075NY01000advertising0000100000c:12241111102.751acquired2.01e+03advertisingadvertising
65       GA33.8-84.4 30303c:1234AtlantaVitrue12006-05-012006-05-012011-02-170     4.8   3.72  7.62  2643.3e+07 5GA00001enterprise0001000000c:12340011103   1acquired2.01e+03enterpriseother_category
139       NH43  -71.5 3101c:149809ManchesterTrendslide12011-08-012011-08-012012-03-010     0.584 0.584 0.595 921.25e+052NH00001mobile0010000000c:1498090100001   0acquired2.01e+03mobilemobile
98       CA40  -105   94025c:13733Menlo ParkPublicEarth02008-01-012011-02-152008-02-082010-05-210.104 2.39  2.33  2.79  724e+06       2CA10000travel0000000001c:137331010001   1closed2.01e+03other_categoryother_category
681       WA47.6-122   98102c:39106SeattleAzaleos12004-05-112007-11-062007-11-063.49  3.49  5.66  8.34  1011e+07       3WA00001enterprise0001000000c:391060000102   1acquired2e+03       enterpriseother_category
884       CA37.4-122   94089c:5306SunnyvaleEfficient Frontier12002-01-012006-08-312006-08-314.67  4.67  8.74  10.2   2516e+06       4CA10000advertising0000100000c:53060000103   1acquired2e+03       advertisingadvertising
747       NY40.7-74   100011c:43188New YorkGo Try It On12009-12-012010-11-042012-11-130.926 2.95  0.833 2.74  233.75e+063NY01000fashion0000000001c:431880110002   1acquired2.01e+03other_categoryother_category
593       MA42.4-71.1 2139c:33507CambridgePerformable12009-10-172010-01-152010-01-150.247 0.247 1.12  1.66  913e+06       2MA00100software1000000000c:335070010001   1acquired2.01e+03softwaresoftware
1.01e+03CA37.8-122   94607c:68157San FranciscoAppstores.com12010-05-242010-08-012011-08-010.189 1.19  1.36  1.66  621.16e+062CA10000software1000000000c:681570100009.5 1acquired2.01e+03softwaresoftware
403       CA37.6-122   94404c:2395San MateoFortify Software12002-10-012005-12-152005-12-153.21  3.21  5.25  7.88  1111e+07       2CA10000software1000000000c:23950000012   1acquired2e+03       softwaresoftware
666       CA37.7-122   94080c:38220South San FranciscoiCurrent12006-01-012008-08-012008-08-012.58  2.58  2     2     513e+06       1CA10000web0100000000c:382200010001   1acquired2.01e+03webweb
847       MA42.4-71.1 2210c:49815BostonAisleBuyer12009-01-012010-11-232011-06-131.89  2.45  2     3.28  421.15e+073MA00100mobile0010000000c:498150000001   1acquired2.01e+03mobilemobile
421       TX30.3-97.8 78731c:249AustinIndeed12004-11-012005-08-012005-08-010.748 0.748 4.05  8.32  1215e+06       5TX00010web0100000000c:2490010003   1acquired2e+03       webweb
364       MA42.4-71.2 2451c:22027WalthamColubris Networks12000-01-012005-03-082006-10-235.19  6.81  7.33  7.33  922.9e+07 1MA00100public_relations0000000001c:220271000015   1acquired2e+03       other_categoryother_category
31       CA37.8-122   94103c:109San FranciscoMashery12006-05-012007-01-012012-07-230.671 6.23  4.05  7.6   3763.47e+074CA10000enterprise0001000000c:1091111115   1acquired2.01e+03enterpriseother_category
1.06e+03CA37.4-122   95128c:765Palo AltoViewdle12006-01-012008-03-012010-10-052.16  4.76  4     6.75  1331.2e+07 2CA10000analytics0000000001c:7651011002   1acquired2.01e+03other_categoryother_category
320       CA33.6-118   92656c:19257Aliso ViejoEnclarity12005-02-012009-03-102009-03-104.1   4.1   1.92  1.92  1815.5e+06 1CA10000consulting0000000010c:192570000102   1acquired2e+03       consultingother_category
445       CA37.4-122   94089c:25827SunnyvaleVirsto Software12007-07-012009-06-262011-08-251.99  4.15  2.9   5.26  1032.4e+07 4CA10000software1000000000c:258270011003.331acquired2.01e+03softwaresoftware
950       MO39.1-94.6 64106c:5932Kansas CityHandmark12000-07-012005-09-122006-09-075.2   6.19  7.51  12.9   621e+07       2MO00001mobile0010000000c:59320011004.5 1acquired2e+03       mobilemobile
1.11e+03CA37.8-122   94111c:8596San FranciscoCarbonetworks02005-01-012011-07-282008-07-012008-07-013.5   3.5   3     3     615e+06       1CA10000cleantech0000000001c:85960010001   1closed2e+03       other_categoryother_category
332       WA47.7-122   98033-6314c:19861KirklandSchemaLogic12001-01-012005-01-172010-04-204.05  9.3   6     6     251.89e+071WA00001enterprise0001000000c:198611000103   1acquired2e+03       enterpriseother_category
396       MA42.4-71.1 02111-1720c:23533BostonCardStar12008-12-012010-03-302011-09-131.33  2.78  1.67  3.13  532.03e+062MA00100software1000000000c:235330010003   1acquired2.01e+03softwaresoftware
431       CA37.8-122   94501c:25325AlamedaMakani Power12006-01-012008-08-232008-08-232.64  2.64  0     7.39  415e+06       2CA10000cleantech0000000001c:253250001001   1acquired2.01e+03other_categoryother_category
13       CO40.7-74   80302c:10392BoulderIntela12006-02-022010-01-182012-08-093.96  6.52  4.58  7.69  421.32e+074CO00001advertising0000100000c:103921000002   0acquired2.01e+03advertisingadvertising
452       CA37.5-122   94403-1855c:26128San MateoSana Security12000-01-012007-04-022007-04-027.25  7.25  7.01  7.01  711.2e+07 1CA10000security0000000001c:261280000002   1acquired2e+03       other_categoryother_category
492       CA37.8-122   94104c:2808San FranciscoSportgenic12005-09-012007-01-012008-09-091.33  3.02  3.02  3.34  931.15e+072CA10000advertising0000100000c:28080111003.331acquired2e+03       advertisingadvertising
20       CA37.8-122   94105c:10581San FranciscoLolapps12008-01-012008-09-052008-09-050.679 0.679 2.92  4.23  1514e+06       3CA10000web0100000000c:105810010003   1acquired2.01e+03webweb
315       CA37.3-122   94087c:190214SunnyvaleBehavio12012-06-122012-06-012012-06-01-0.0301-0.03010.137 0.137 313.55e+051CA10000software1000000000c:1902140100001   0acquired2.01e+03softwaresoftware
231       FL28.1-82.4 33626c:1674TampaInfinity Box12006-01-012006-01-012006-04-010     0.247 2.42  5.32  1021.18e+053FL00001web0100000000c:16740100001.5 1acquired2.01e+03webweb
245       CA37.8-122   94103c:170San FranciscoadBrite12003-01-012001-02-012004-09-012012-05-011.67  9.34  7.38  10.5   1744.04e+073CA10000advertising0000100000c:1700011111.671acquired2e+03       advertisingadvertising
810       CA37.5-122   94538c:46186FremontMendocino Software02003-01-012008-02-072005-09-122007-01-012.7   4     1     1     221.97e+071CA10000software1000000000c:461861001004   1closed2e+03       softwaresoftware
748       CA37.8-122   94107c:43233San FranciscoInstagram12010-03-012010-03-052012-04-050.011 2.1   3.09  3.78  1235.75e+073CA10000photo_video0000000001c:432330111004   1acquired2.01e+03other_categoryother_category
138       NY40.6-73.8 10004c:1498New YorkMotionbox12006-01-012006-09-012009-01-140.666 3.04  2     5.05  1031.72e+075NY01000games_video0000010000c:14980011102.671acquired2.01e+03games_videogames_video
555       MA42.4-71.1 2138c:31514CambridgeAccelGolf02008-08-012013-05-012008-01-012009-12-04-0.584 1.34  0     1.55  474.57e+052MA00100mobile0010000000c:315141100001   1closed2.01e+03mobilemobile
943       CA37.8-122   94105c:58944San FranciscoMoPub12010-09-092010-09-012012-09-20-0.02192.03  2.32  3.16  1141.85e+073CA10000mobile0010000000c:589440111002.251acquired2.01e+03mobilemobile
863       CO40.4-105   80538c:51023LovelandAbound Solar02007-01-012012-11-012010-07-062010-12-153.51  3.96  3.95  4.84  525.1e+08 3CO00001cleantech0000000001c:510231000002.5 1closed2.01e+03other_categoryother_category
85       CA37.4-122   94043c:13168Mountain ViewTrovix12002-01-012005-12-072006-09-063.93  4.68  4     4     321.82e+071CA10000search0000000001c:131680011002.5 1acquired2e+03       other_categoryother_category
995       NY40.7-74   10012c:649New YorkThumbplay12004-09-012006-10-302010-04-212.16  5.64  3.83  7.69  1344.15e+075NY01000music0000000001c:6490000104   1acquired2e+03       other_categoryother_category
541       CA34  -118   90025c:3080Los AngelesDailyStrength12006-04-012007-05-182007-05-181.13  1.13  1     2.68  715e+06       2CA10000web0100000000c:30800010001   1acquired2.01e+03webweb
501       MI42.4-83.4 48187c:28424CantonDanotek Motion Technologies02001-01-012013-05-012008-11-192011-08-307.89  10.7   0.414 0.414 234.27e+071MI00001cleantech0000000001c:284241001003.671closed2e+03       other_categoryother_category
537       WA47.6-122   98004c:30537BellevueSNAPin Software12003-01-012005-07-112006-02-072.53  3.1   3     9.13  522.23e+072WA00001software1000000000c:305370001104.5 1acquired2e+03       softwaresoftware
125       CA37.4-122   95054c:14656Santa ClaraAzuro12002-01-012006-01-012009-11-134     7.87  0.162 0.162 521e+07       1CA10000semiconductor0000000001c:146561001004   1acquired2e+03       other_categoryother_category
242       CA37.8-122   94105c:16938San FranciscoBookFresh12007-01-012009-07-282009-07-282.57  2.57  2.48  4.67  715e+05       2CA10000web0100000000c:169380100005   1acquired2.01e+03webweb
1.1e+03 CA37.8-122   94110c:83265San FranciscoSingly12010-12-212011-02-012012-04-230.115 1.34  1.83  2.67  2428.95e+062CA10000analytics0000000001c:832650010007   1acquired2.01e+03other_categoryother_category
387       NY40.8-74   10173c:23136New YorkTxVia12006-01-012007-10-012010-10-261.75  4.82  4     4.82  845.54e+072NY01000finance0000000001c:231360011114   1acquired2.01e+03other_categoryother_category
251       IL41.9-87.6 60606c:17219ChicagoOpen Kernel Labs12006-01-012007-09-132012-07-061.7   6.52  3.28  4.93  351.08e+073IL00001software1000000000c:172191010002   1acquired2.01e+03softwaresoftware
390       NJ40.5-74.5 8873c:23234SomersetElanti Systems02007-01-012012-02-112008-05-292008-05-291.41  1.41  0     0     115.5e+06 1NJ00001software1000000000c:232341000003   1closed2.01e+03softwaresoftware
1.02e+03CA37.8-122   94105c:70586San FranciscoAstrid12008-01-012012-04-132012-04-134.28  4.28  2.42  5.52  714e+05       2CA10000social0000000001c:705860100003   1acquired2.01e+03other_categoryother_category
670       CA37.3-122   95128c:38338San Jose41st Parameter12004-01-012006-05-082012-04-112.35  8.28  1     8.28  1643.81e+072CA10000security0000000001c:383381001113   1acquired2e+03       other_categoryother_category
811       CA37.7-122   94110c:4622San FranciscoAardvark12007-07-012011-09-012007-01-012008-10-01-0.496 1.25  2.17  4.6   2126e+06       2CA10000web0100000000c:46220110004   1acquired2.01e+03webweb
339       VA38  -78.5 22902c:202CharlottesvilleHotelicopter02006-06-012012-08-012008-11-172011-03-312.47  4.83  0.586 5.62  425e+06       6VA00001web0100000000c:2020011001   0closed2.01e+03webweb
163       VA39  -77.4 20166c:15652DullesAnystream12000-01-012000-01-012007-02-070     7.11  6.01  10.9   935.9e+07 3VA00001software1000000000c:156521000102   1acquired2e+03       softwaresoftware
121       IL39.8-100   60607c:144825ChicagoCakeStyle02011-08-012013-08-012012-08-132012-08-131.04  1.04  0     1.04  211e+06       2IL00001web0100000000c:1448250100001   0closed2.01e+03webweb
1.15e+03CA37.8-122   94110c:9772San FranciscoFluther12007-01-012009-09-212009-09-212.72  2.72  0.915 6.31  516e+05       3CA10000web0100000000c:97720100007   1acquired2.01e+03webweb
316       CT41.9-72.7 6002c:19101BloomfieldPocket Communications Northeast02006-01-012012-01-012008-11-012009-02-202.84  3.14  3.38  3.78  021.25e+082CT00001mobile0010000000c:191010011002   1closed2.01e+03mobilemobile
187       CA34  -118   60401c:1612Santa MonicaGoodreads12007-01-152007-11-012009-12-090.794 2.9   3.05  6.52  1122.75e+063CA10000web0100000000c:16120110004   1acquired2.01e+03webweb
695       CA37.5-122   94025c:3986Menlo ParkKrugle12006-01-012006-05-312006-05-310.411 0.411 0     2.53  1016.1e+06 2CA10000search0000000001c:39860001004   1acquired2.01e+03other_categoryother_category
973       CA32.7-117   92101c:61592San DiegoFlud02010-10-012013-08-082011-04-132012-09-010.531 1.92  2.25  2.98  1232.1e+06 2CA10000enterprise0001000000c:615921100004   1closed2.01e+03enterpriseother_category
618       CA37.8-122   94103c:35236San FranciscoChomp12009-09-092009-11-012010-03-110.145 0.501 0.496 3.01  1022.56e+063CA10000mobile0010000000c:352360110003.5 1acquired2.01e+03mobilemobile
483       NC35.8-78.7 27606c:27620RaleighInlet Technologies12003-01-012005-07-262008-09-082.57  5.69  2     2     332.24e+071NC00001network_hosting0000000001c:276201001103.671acquired2e+03       other_categoryother_category
1.15e+03NY40.7-74   10011c:9816New YorkShopWiki12005-06-012006-07-012006-07-011.08  1.08  6     6     1216.25e+061NY01000ecommerce0000001000c:98160010001   0acquired2e+03       ecommerceecommerce
881       NY40.8-74   10001c:52566New YorkFondu12010-02-012011-11-012011-11-011.75  1.75  1     2.11  415.75e+052NY01000web0100000000c:525660100006   0acquired2.01e+03webweb
841       MA42.4-71.1 2143c:49236SomervilleLoudcaster02009-08-012012-01-012009-08-012010-03-010     0.581 0     0     125.3e+04 1MA00100web0100000000c:492360100001   1closed2.01e+03webweb
370       CA37.5-122   94065c:2234Redwood CityTwoFish12006-01-012006-12-012008-10-100.915 2.78  3     3.65  629.5e+06 2CA10000ecommerce0000001000c:22340011002.5 1acquired2.01e+03ecommerceecommerce
506       CA37.5-122   94538c:28482FremontRedwood Systems12008-01-012008-10-032012-05-300.756 4.41  2.78  4     1443.42e+072CA10000cleantech0000000001c:284821011102.251acquired2.01e+03other_categoryother_category
179       MD39.4-76.6 21093c:1595TimoniumBill Me Later12000-01-012006-03-012007-12-016.17  7.92  8.01  11.3   631e+08       3MD00001web0100000000c:15951010002.5 1acquired2e+03       webweb
550       PA40.4-80   15213c:31294PittsburghBueda02009-01-042013-06-012008-01-012010-07-01-1.01  1.49  0.406 1.32  321.25e+052PA00001advertising0000100000c:312941100001   1closed2.01e+03advertisingadvertising
764       VA39  -77.4 20191c:43875RestonDefywire02003-01-012008-05-012005-04-262007-03-272.32  4.24  -0.334 -0.334 221.06e+071VA00001mobile0010000000c:438751001003   1closed2e+03       mobilemobile
218       CA37.6-122   94538c:16562FremontSilicon Clocks12004-01-012006-06-022009-06-082.42  5.44  2     2     232.61e+071CA10000semiconductor0000000001c:165621001003.5 1acquired2e+03       other_categoryother_category
299       NY40.8-74   10019c:18075New YorkTheMarkets12000-01-012007-07-122007-07-127.53  7.53  10.7   10.7   213e+07       1NY01000web0100000000c:180751000005   1acquired2e+03       webweb
1.11e+03IL41.9-87.6 60606c:86120ChicagoNetgamix Inc02010-09-242012-04-032011-10-152012-07-011.06  1.77  1.03  1.11  631.33e+052IL00001games_video0000010000c:861200100001   1closed2.01e+03games_videogames_video
782       CA37.4-122   94303c:44650Palo AltoNetli12000-01-012006-02-132006-02-136.12  6.12  6.01  6.01  911.8e+07 1CA10000network_hosting0000000001c:446501000007   1acquired2e+03       other_categoryother_category
1.02e+03OH39.1-84.5 45202c:70021CincinnatiDefine My Style02010-02-012012-01-012011-12-022011-12-021.83  1.83  1.75  1.75  416.9e+05 1OH00001web0100000000c:700210100003   1closed2.01e+03webweb
430       MA42.4-71.1 2142c:25324CambridgeTaligen Therapeutics12004-01-012005-08-012010-08-231.58  6.65  5.01  7.09  437.88e+072MA00100biotech0000000100c:253240011003.5 1acquired2e+03       biotechother_category
1.06e+03CA37.6-122   94403c:77San MateoAdap.tv12006-11-012007-02-012011-03-280.252 4.41  3.32  6.79  2754.85e+073CA10000advertising0000100000c:771111102.5 1acquired2.01e+03advertisingadvertising
312       CA37.8-122   94107c:1895San FranciscoCurrent Media02005-01-012013-08-202005-07-292005-07-290.573 0.573 5.17  8.01  1211.5e+07 2CA10000network_hosting0000000001c:18950010003   0closed2e+03       other_categoryother_category
206       CA37.8-122   94107-4132c:16289San FranciscoArch Rock Corporation12005-01-012005-10-012007-05-020.748 2.33  2     2     621.5e+07 1CA10000software1000000000c:162890011003   1acquired2e+03       softwaresoftware
928       NY37.1-95.7 10014c:575New YorkSpiralFrog02004-01-012009-03-202006-01-012007-12-012     3.92  3     5.22  834.5e+07 3NY01000games_video0000010000c:5750010001   0closed2e+03       games_videogames_video
158       CA37.4-122   95054c:15562Santa ClaraPlusmo12006-06-012008-05-012008-05-011.92  1.92  2     2     414.41e+061CA10000mobile0010000000c:155620010001   1acquired2.01e+03mobilemobile
979       VA39  -77.4 20166c:62432SterlingZipList12010-01-012010-01-012010-11-240     0.896 2     2.68  924.5e+06 2VA00001web0100000000c:624320011002   1acquired2.01e+03webweb
1.08e+03CA37.8-122   94105c:8100San FranciscoInvolver12007-01-012008-09-022010-10-141.67  3.79  4.67  5.68  1131.1e+07 2CA10000software1000000000c:81000011102.5 1acquired2.01e+03softwaresoftware
977       CA37.8-122   94107c:62262San FranciscoLionside12009-01-012010-11-192010-11-191.88  1.88  1.33  2.95  611.6e+06 2CA10000games_video0000010000c:622620010003   1acquired2.01e+03games_videogames_video
639       NY40.7-74   10011c:3686New YorkGame Trust12002-01-012005-06-012005-11-153.42  3.87  7.75  7.75  329e+06       1NY01000software1000000000c:36861001004   1acquired2e+03       softwaresoftware
1.09e+03CA37.5-122   94403c:82805San MateoNearbuy Systems12010-04-012011-07-212012-11-231.3   2.65  0     3.68  433.28e+062CA10000analytics0000000001c:828051000002   1acquired2.01e+03other_categoryother_category
327       CA37.6-122   94404c:196Foster CityVisible Path12002-01-012006-03-012006-03-014.16  4.16  5.58  11.4   522.47e+075CA10000web0100000000c:1960011004   1acquired2e+03       webweb
87       CA34  -118   90025c:13277Los AngelesGetBack02007-09-012010-11-222008-11-062008-11-061.18  1.18  0.918 0.918 111.7e+06 1CA10000web0100000000c:132770010001   0closed2.01e+03webweb
985       CA37.8-122   94609c:63217OaklandSlipstream02010-06-012013-05-012010-08-312010-08-310.249 0.249 0     0.778 112e+04       2CA10000web0100000000c:632170100001   0closed2.01e+03webweb
432       CA37.6-122   94538c:2534FremontHipLogic12005-01-012008-02-082009-12-023.1   4.92  5     8.35  1021.15e+075CA10000mobile0010000000c:25340011002.5 1acquired2e+03       mobilemobile
882       CA38.3-123   94954c:5264PetalumaDilithium Networks02001-01-012012-10-012003-04-232010-06-032.31  9.42  4.5   11.4   1279.82e+073CA10000mobile0010000000c:52641001115.2 1closed2e+03       mobilemobile
937       CA37.8-122   94107c:58512San FranciscoYobongo12010-01-012011-03-232011-03-231.22  1.22  0.748 2.68  211.35e+063CA10000web0100000000c:5851201000010   1acquired2.01e+03webweb
77       IL41.9-87.6 60601c:12957ChicagoBrickfish12005-11-012010-07-162010-07-164.71  4.71  2.99  6.86  1719.4e+05 2IL00001software1000000000c:129570010001   1acquired2e+03       softwaresoftware
608       MA42.4-71.1 2109c:34499BostonMyEnergy12007-06-042009-02-012011-02-031.67  3.67  3.67  3.67  1224e+06       3MA00100web0100000000c:344990110003   1acquired2.01e+03webweb
601       CA37.4-122   94085c:34028SunnyvaleLikeList02008-01-012012-12-062009-12-152009-12-151.96  1.96  1     1     515e+06       1CA10000web0100000000c:340280010001   0closed2.01e+03webweb
392       VA38.9-77.1 22201c:23335ArlingtonSocial Collective02009-04-172012-03-062009-04-182009-04-180.00270.00270.584 0.584 312e+04       1VA00001web0100000000c:233350100001   0closed2.01e+03webweb
535       WA47.6-122   98101c:30526SeattlePure Networks12002-01-012006-01-112006-01-114.03  4.03  3     3     511.25e+071WA00001network_hosting0000000001c:305260001003   1acquired2e+03       other_categoryother_category
736       CO39.6-105   80112c:42519CentennialInternet Pawn02009-01-012013-03-012010-05-052013-08-271.34  4.65  1.36  1.38  057.23e+062CO00001finance0000000001c:425191010002   1closed2.01e+03other_categoryother_category
836       IL41.9-87.8 60631c:48376ChicagoNeuroTherapeutics Pharma02006-01-012013-06-012010-05-202011-12-154.38  5.96  5.5   5.5   525.5e+07 1IL00001biotech0000000100c:483761001004   1closed2.01e+03biotechother_category
828       CA37.4-122   95134c:47587San JoseInfineta Systems02008-01-012012-01-012010-05-072011-06-062.35  3.43  2.36  4     423e+07       2CA10000software1000000000c:475870011002.5 1closed2.01e+03softwaresoftware
227       TX30.3-97.7 78701c:1669AustinChallenge Games12006-01-012008-07-102008-09-012.52  2.67  3     4.42  1121.45e+073TX00010network_hosting0000000001c:16690011001.5 1acquired2.01e+03other_categoryother_category
725       CA37.8-122   94114c:421San FranciscoCrowd Factory12009-01-012011-01-262011-01-262.07  2.07  2.58  4.37  616.5e+06 3CA10000advertising0000100000c:4211000003   1acquired2.01e+03advertisingadvertising
159       TN35.1-90.1 38103-4717c:155621MemphisFriendsignia02012-01-292013-06-012012-01-292012-01-290     0     0     0     211.5e+04 1TN00001web0100000000c:1556210100001   0closed2.01e+03webweb
709       NY40.7-74   10013c:40782New YorkVizibility12009-07-012010-03-242013-02-060.729 3.61  1.59  4.1   554.71e+063NY01000mobile0010000000c:407821100003   1acquired2.01e+03mobilemobile
868       CA37.6-122   94010-4031c:51306BurlingameOpenFeint12008-01-012010-10-212010-10-212.81  2.81  3     4.65  613e+06       2CA10000games_video0000010000c:513061000001   1acquired2.01e+03games_videogames_video
30       NY40.7-74   10016c:1088New YorkTumblr12007-02-012007-10-312012-01-010.745 4.92  3.04  6.84  3061.25e+085NY01000web0100000000c:10881011113.5 1acquired2.01e+03webweb
609       NY40.7-74   10013c:34522New YorkHotlist02008-01-012013-05-012008-05-012012-01-010.332 4     2.36  3.67  841.45e+063NY01000social0000000001c:345221100001   1closed2.01e+03other_categoryother_category
1.1e+03 MA42.4-71.1 2139c:83692CambridgeCrashlytics12011-02-012011-10-132012-04-100.696 1.19  0.663 2.62  526e+06       3MA00100mobile0010000000c:836920110006   1acquired2.01e+03mobilemobile
502       CA37.8-122   94104c:28428San FranciscoRecurve12005-08-012008-09-232010-06-173.15  4.88  5     5     521.4e+07 1CA10000software1000000000c:284281010002   1acquired2e+03       softwaresoftware
295       TX30.4-97.8 78730c:17974AustinConformity02007-07-012009-01-012009-01-282009-01-281.58  1.58  2.25  2.53  1413e+06       2TX00010enterprise0001000000c:179740010001   0closed2.01e+03enterpriseother_category
1.09e+03WA39.8-100   98104c:81475SeattleMoprise02010-01-012013-07-012011-07-082011-10-071.52  1.76  0.748 0.748 622.24e+061WA00001enterprise0001000000c:814751100001   1closed2.01e+03enterpriseother_category
1.06e+03CA37.8-122   94108c:76543San FranciscoPlizy02010-09-012013-06-012011-05-192012-12-130.712 2.28  1.95  2.28  525.2e+06 2CA10000photo_video0000000001c:765431010001   1closed2.01e+03other_categoryother_category
1.1e+03 PA40.1-75.3 19428c:84161ConshohockenShopRunner12010-01-012013-08-192013-08-193.63  3.63  1.15  3.78  417.5e+07 4PA00001ecommerce0000001000c:841611000001   0acquired2.01e+03ecommerceecommerce
1.08e+03MA42.3-71.2 2494c:810NeedhamRatePoint02006-09-012012-02-022007-01-292010-08-200.411 3.97  4.25  5.77  1342.45e+074MA00100software1000000000c:8100011102.5 1closed2.01e+03softwaresoftware
35       TX30.3-97.7 78701c:11042AustinGowalla12007-08-282008-02-272010-01-280.501 2.42  2.82  5.88  2131.04e+073TX00010web0100000000c:110420011006   1acquired2.01e+03webweb
276       CO40.1-105   80501c:17633LongmontCopan Systems12002-01-012006-03-082009-02-174.18  7.13  5     5     836.84e+071CO00001network_hosting0000000001c:176331000116.5 1acquired2e+03       other_categoryother_category
901       IL41.8-88.1 60563c:54585NapervilleCartavi12009-01-012012-11-132012-11-133.87  3.87  3.83  4.09  711.23e+062IL00001enterprise0001000000c:545850100001   1acquired2.01e+03enterpriseother_category
46       CA34.1-118   91101c:11507PasadenaCramster12002-01-012008-09-252010-04-146.74  8.29  6.75  6.75  529e+06       1CA10000web0100000000c:115070011001   0acquired2e+03       webweb
419       CA37.3-122   95128c:24860San JoseCertify Data Systems12004-01-012008-08-252012-02-154.65  8.13  6.01  6.01  447.21e+061CA10000enterprise0001000000c:248601011001   0acquired2e+03       enterpriseother_category
135       CA37.8-122   94103c:148750San FranciscoWheelz12011-01-012011-09-282012-02-220.74  1.14  0.581 0.581 1521.57e+071CA10000automotive0000000001c:1487500010003   1acquired2.01e+03other_categoryother_category
798       MA42.4-71.2 2451c:45611WalthamCentrePath12000-01-012005-09-062006-04-245.68  6.32  5.01  5.01  421.5e+07 1MA00100software1000000000c:456111000102.5 1acquired2e+03       softwaresoftware
712       CA37.8-122   94111c:4106San FranciscoVoxPop Network Corporation12006-08-012007-05-012009-05-010.748 2.75  1.58  4.53  523.5e+06 2CA10000games_video0000010000c:41060011003   1acquired2.01e+03games_videogames_video
286       CA37.4-122   95035c:17775MilpitasOpVista02000-01-012009-08-012006-06-222007-05-076.48  7.35  5.01  5.01  224.3e+07 1CA10000software1000000000c:177750000111   1closed2e+03       softwaresoftware
115       CA37.8-122   94105c:144San FranciscoMetaweb Technologies12005-01-012006-03-012008-01-151.16  3.04  3.27  5.54  725.7e+07 2CA10000web0100000000c:1440011003.5 1acquired2e+03       webweb
81       CA37.8-122   94105c:13046San FranciscoDocVerse12007-09-012008-07-232008-07-230.893 0.893 0.833 4.21  811.3e+06 4CA10000web0100000000c:130460100004   1acquired2.01e+03webweb
699       CA32.9-117   92121c:40San DiegoVeoh12004-01-012005-07-012008-06-031.5   4.42  4.09  9.74  1546.98e+074CA10000games_video0000010000c:400011115   1acquired2e+03       games_videogames_video
456       MA42.3-71.1 2118c:26460BostonBzzAgent12001-01-012004-01-012006-01-013     5     9.62  10.4   1621.45e+072MA00100advertising0000100000c:264600101002   1acquired2e+03       advertisingadvertising
691       CA37.8-122   94404c:3962San MateoGuardianEdge Technologies12002-01-012005-06-062007-07-233.43  5.56  7.84  7.84  1031.95e+071CA10000software1000000000c:39620011003.331acquired2e+03       softwaresoftware
196       CA34  -118   90405c:162116Santa MonicaGradient X12012-01-012012-06-202012-06-200.469 0.469 1.1   1.68  513.75e+063CA10000mobile0010000000c:1621160000009   1acquired2.01e+03mobilemobile
1.03e+03NC35.8-78.7 27607c:7207RaleighrPath02005-04-012013-05-012006-01-242010-10-220.816 5.56  4.56  7.99  843.25e+073NC00001enterprise0001000000c:72070011112.751closed2e+03       enterpriseother_category
1.12e+03PA40.1-75.5 19312c:863BerwynBoomi12000-03-012002-01-012008-07-011.84  8.34  5.67  13.6   424.9e+06 5PA00001enterprise0001000000c:8630101001.5 1acquired2e+03       enterpriseother_category
183       CA37.4-122   94086c:16066SunnyvaleVoloMedia02005-01-012011-02-032007-04-202008-03-182.3   3.21  3.59  4.58  421.2e+07 3CA10000advertising0000100000c:160660001102   1closed2e+03       advertisingadvertising
363       CA37.8-122   94103c:220San FranciscoFlixster12006-01-202006-02-012008-04-040.03292.21  4.52  6.91  1237.18e+066CA10000web0100000000c:2200111002.671acquired2.01e+03webweb
894       CA37.8-122   94104c:54San FranciscoWesabe02005-12-012010-06-302007-02-012007-06-011.17  1.5   0.08495.39  324.7e+06 4CA10000web0100000000c:540110001.5 1closed2e+03       webweb
549       CA37.4-122   94041c:3122Mountain ViewNeoEdge Networks12002-05-022007-06-082010-12-205.1   8.64  5.67  6.9   1031e+07       2CA10000advertising0000100000c:31221001001.670acquired2e+03       advertisingadvertising
291       CA37.8-122   94115c:1789San FranciscoNuConomy12006-01-012007-04-012008-02-011.25  2.08  2.5   5.32  423.3e+06 3CA10000advertising0000100000c:17890110002   1acquired2.01e+03advertisingadvertising
671       CA37.8-122   94110c:38339San FranciscoFlowtown12009-02-012010-08-252010-08-251.56  1.56  1.24  1.77  617.5e+05 3CA10000analytics0000000001c:383390100009   1acquired2.01e+03other_categoryother_category
587       CA34  -118   90094c:3288Playa VistaWebVisible02001-01-012011-10-012005-09-012010-02-114.67  9.12  9.75  12.8   3333.7e+07 4CA10000software1000000000c:32880011101.331closed2e+03       softwaresoftware
7       CA37.8-122   94111c:10179San FranciscoGoodGuide12007-12-012009-01-192011-08-261.14  3.74  2.46  3.22  1431.42e+073CA10000web0100000000c:101790011003   1acquired2.01e+03webweb
596       CA37.3-122   95014c:33869CupertinoViVu12009-01-012009-09-212011-06-090.721 2.44  0.767 2.79  723e+06       2CA10000messaging0000000001c:338690011002.5 1acquired2.01e+03other_categoryother_category
356       NY40.7-74   10013c:21528New YorkavVenta12005-01-012009-01-142009-01-144.04  4.04  6     6     1012e+07       1NY01000advertising0000100000c:215280010001   0acquired2e+03       advertisingadvertising
542       RI51.4-2.662906c:30820ProvidenceDiJiPOP12008-11-012009-08-012010-12-060.748 2.1   1.65  2.1   622e+06       3RI00001advertising0000100000c:308200100001.5 1acquired2.01e+03advertisingadvertising
443       DC38.9-77   20005c:25782WashingtonLayer 7 Technologies12003-01-012006-10-262009-02-023.82  6.09  9.01  9.77  321.99e+072DC00001software1000000000c:257821001002   1acquired2e+03       softwaresoftware
487       CA37.8-122   94107c:278San FranciscoDeliveryEdge02006-09-012009-04-012007-12-012007-12-011.25  1.25  2.59  2.59  611.5e+06 1CA10000ecommerce0000001000c:2780000001   0closed2.01e+03ecommerceecommerce
1.05e+03CA37.8-122   94105c:75500San FranciscoSolmentum02009-07-012011-11-092009-07-012009-07-010     0     1.25  1.25  413.25e+051CA10000cleantech0000000001c:755000100004   0closed2.01e+03other_categoryother_category
1.01e+03CA37.8-122   94105c:67806San FranciscoPipewise02010-09-012012-10-012011-02-172011-02-170.463 0.463 1.28  1.82  1613.5e+06 2CA10000enterprise0001000000c:678060010005   1closed2.01e+03enterpriseother_category
55       WA47.6-122   98104c:1212SeattleGridNetworks02004-01-012012-08-172006-01-012008-05-202     4.39  1.58  4.19  743e+07       2WA00001network_hosting0000000001c:12120111002   1closed2e+03       other_categoryother_category
429       NY40.7-74   10016c:25307New YorkORCA, Inc.12008-01-012009-06-212009-06-211.47  1.47  1     1.47  512e+06       2NY01000ecommerce0000001000c:253070010003   1acquired2.01e+03ecommerceecommerce
307       CA37.5-122   94065c:1870Redwood CityAmobee12005-05-012006-11-012011-03-011.5   5.84  6.17  8.35  2567.2e+07 2CA10000advertising0000100000c:18701011112.331acquired2e+03       advertisingadvertising
475       CA34  -118   91754c:27285Monterey ParkKOTURA12004-01-012005-09-072009-11-051.68  5.85  8.42  8.42  432.77e+071CA10000cleantech0000000001c:272850001114.5 1acquired2e+03       other_categoryother_category
305       CA37.3-122   94041c:18470Mountain ViewOutright12008-06-012008-11-012009-11-180.419 1.47  3.13  4.14  1227.5e+06 3CA10000enterprise0001000000c:184700010003.5 1acquired2.01e+03enterpriseother_category
354       TX30.3-97.7 78701c:21395AustinPhurnace Software12007-01-012007-09-112008-07-010.693 1.5   3.42  3.42  921e+07       1TX00010software1000000000c:213950010002   1acquired2.01e+03softwaresoftware
426       CA34.1-118   91105c:25132PasadenaFastSoft12006-01-012007-06-112012-09-041.44  6.68  2     2     745.96e+061CA10000software1000000000c:251321010001   0acquired2.01e+03softwaresoftware
1.03e+03CA37.5-122   94538c:72FremontGrandCentral12006-04-012006-01-012006-01-01-0.247 -0.247 -0.408 7.45  914e+06       4CA10000mobile0010000000c:720010001   0acquired2.01e+03mobilemobile
261       MI42.5-83.2 48025c:17429Bingham FarmsSpeedshape02003-01-012013-08-012008-02-202008-02-205.14  5.14  7.01  7.01  215e+06       1MI00001advertising0000100000c:174291000001   0closed2e+03       advertisingadvertising
838       CA37.3-122   95128c:487San JoseBlueLithium12004-01-012005-02-012005-02-011.09  1.09  5.1   7.39  1511.15e+072CA10000advertising0000100000c:4870010002   1acquired2e+03       advertisingadvertising
707       IL41.9-87.6 60657c:40665ChicagoMedia Chaperone02009-01-012013-06-012010-01-142011-02-241.04  2.15  1.58  1.58  221.05e+061IL00001web0100000000c:406651000001   0closed2.01e+03webweb
523       NY40.8-74   10036c:2972New YorkGiant Realm12007-01-012008-03-012008-05-081.16  1.35  1.35  3.33  1325.5e+06 2NY01000web0100000000c:29720010002   1acquired2.01e+03webweb
303       PA40  -75.2 10011c:1832PhiladelphiaInvite Media12007-02-012007-12-012009-12-010.83  2.83  1.09  3.34  1735e+06       4PA00001advertising0000100000c:18320110001.671acquired2.01e+03advertisingadvertising
1.1e+03 MA42.4-71.1 2129c:833BostonEons02005-01-012012-05-172006-04-012007-03-011.25  2.16  2     3.81  1423.2e+07 4MA00100network_hosting0000000001c:8330011003.5 1closed2e+03       other_categoryother_category
971       MA42.4-71.1 2142c:615CambridgeLocaModa12007-01-012007-09-182011-03-250.712 4.23  2.67  3.06  837.9e+06 2MA00100advertising0000100000c:6150010002   0acquired2.01e+03advertisingadvertising
258       CA37.4-122   94110c:1731San FranciscoMeraki12006-04-012006-12-012012-07-100.668 6.28  2.79  7.45  1658e+07       3CA10000network_hosting0000000001c:17310111112.251acquired2.01e+03other_categoryother_category
693       TX30.3-97.7 78701c:39755AustinMPOWER Mobile02005-01-012012-06-082009-10-282009-10-284.82  4.82  0.247 0.247 115e+06       1TX00010mobile0010000000c:397551000001   1closed2e+03       mobilemobile
89       WA47.6-122   98109c:134SeattleHaute Secure12006-01-012007-01-012009-03-091     3.19  2.43  7.62  522.1e+06 3WA00001security0000000001c:1340110001.5 1acquired2.01e+03other_categoryother_category
984       MD39.1-77.2 20814c:6313BethesdaIntelliworks12004-12-012005-02-142009-04-240.205 4.4   3.42  3.42  642.22e+071MD00001enterprise0001000000c:63130011112.5 1acquired2e+03       enterpriseother_category
437       NY40.7-74   10016c:2566New YorkKluster12008-01-012008-01-012008-01-010     0     3.59  4.33  011e+06       2NY01000web0100000000c:25660100001   1acquired2.01e+03webweb
770       NY37.5-122   10016c:44New YorkJingle Networks12005-09-012005-10-012009-12-280.08224.33  3.66  5.61  1278.87e+075NY01000mobile0010000000c:441111113.171acquired2e+03       mobilemobile
1.1e+03 CA34.1-118   90017c:83176Los AngelesItsGoinOn02010-05-012011-11-012011-01-012011-01-010.671 0.671 0     0.756 311e+05       2CA10000games_video0000010000c:831760100001   0closed2.01e+03games_videogames_video
343       CO39.8-105   80202c:20488DenvermSnap12005-06-012006-06-012006-06-011     1     3.81  4.92  615e+06       3CO00001mobile0010000000c:204880010001   1acquired2e+03       mobilemobile
344       CA37.4-122   94043c:20506Mountain ViewArdian12003-01-012005-01-012009-03-232     6.23  4     10.8   836.41e+072CA10000biotech0000000100c:205060011104   1acquired2e+03       biotechother_category
1.02e+03RI51.4-2.662903c:69279ProvidenceTracelytics12010-07-012011-11-032012-03-221.34  1.73  -0.08221.72  825.8e+06 2RI00001enterprise0001000000c:692790110004   1acquired2.01e+03enterpriseother_category
389       CA37.8-122   94105c:23192San FranciscoCanopy Financial02004-01-012009-08-272008-01-012009-10-014     5.75  5.92  6     648.95e+072CA10000finance0000000001c:231920001101   1closed2e+03       other_categoryother_category
661       CA37.8-122   94102c:38San FranciscoKyte12006-12-012007-07-012012-03-010.581 5.25  3.09  4.17  1142.34e+072CA10000games_video0000010000c:380111003   1acquired2.01e+03games_videogames_video
185       MA42.5-71.5 1719c:16070BoxboroughCrossbeam Systems12000-01-012007-05-082008-02-147.35  8.13  11     11.1   1322.45e+072MA00100security0000000001c:160700000005.5 1acquired2e+03       other_categoryother_category
890       CA37.5-122   94065c:53814Redwood CityPacketHop02002-01-012013-01-042005-08-082005-08-083.6   3.6   3     3     211e+07       1CA10000public_relations0000000001c:538140000104   1closed2e+03       other_categoryother_category
708       CA37.4-122   94306c:40762Palo AltoImmunet Corporation12008-07-012009-11-012009-11-011.34  1.34  1.35  1.35  312e+06       1CA10000software1000000000c:407620010002   1acquired2.01e+03softwaresoftware
1.05e+03TX30.3-97.7 78701c:75008AustinCopperEgg Corporation12010-06-012011-07-122012-05-081.11  1.94  0     1.11  324.1e+06 2TX00010enterprise0001000000c:750080010001.5 1acquired2.01e+03enterpriseother_category
330       CA37.4-122   94041c:197Mountain ViewWink12004-08-192005-01-012005-01-010.37  0.37  1.95  8.32  516.2e+06 4CA10000search0000000001c:1970010002   1acquired2e+03       other_categoryother_category
544       CA37.8-122   94103c:3087San FranciscoPopularMedia12003-01-012007-02-012008-07-284.09  5.58  4     4     821.22e+071CA10000advertising0000100000c:30870001102.5 1acquired2e+03       advertisingadvertising
383       CA37.8-122   94105c:23098San FranciscoMiyowa12003-04-142006-09-042008-05-083.39  5.07  5.72  8.73  321.17e+072CA10000mobile0010000000c:230980011002   1acquired2e+03       mobilemobile
646       WA47.6-122   98103c:37215SeattleDashwire12006-08-112009-01-312010-12-282.48  4.38  3.39  4.99  1035.06e+062WA00001mobile0010000000c:372151010001.671acquired2.01e+03mobilemobile
552       CA37.8-122   94107c:314San FranciscoReddit12005-01-012005-06-012005-06-010.414 0.414 6.83  8.87  911e+05       3CA10000web0100000000c:3140100001   1acquired2e+03       webweb
697       CA37.8-122   94108c:3991San FranciscoPure Digital Technologies12001-09-012004-01-012008-08-182.33  6.97  4     8.3   1136.82e+073CA10000hardware0000000001c:39911100004   1acquired2e+03       other_categoryother_category
239       CA37.8-122   94501c:16892AlamedaVoxify12001-01-012005-02-012010-04-214.09  9.31  6     6     533.3e+07 1CA10000enterprise0001000000c:168921001013.671acquired2e+03       enterpriseother_category
672       NC36  -78.9 27701c:38460DurhamEvoApp02009-01-012013-01-012010-10-152012-04-201.79  3.3   2.08  2.33  833.35e+062NC00001analytics0000000001c:384600110009.5 0closed2.01e+03other_categoryother_category
996       NY40.8-74   10001c:64959New YorkVisual Revenue12010-03-012011-07-282012-01-261.41  1.91  -0.162 1.84  522.21e+062NY01000analytics0000000001c:649590110003   1acquired2.01e+03other_categoryother_category
825       CA37.6-122   94401c:47270San MateoOffermatic02010-02-012013-06-012010-12-012011-03-090.83  1.1   1.1   1.16  624.5e+06 2CA10000web0100000000c:472700110003   1closed2.01e+03webweb
263       MA42.3-71.2 2494c:17433NeedhamHiWired12004-01-012008-01-012008-01-024     4.01  4     4     221.4e+07 1MA00100software1000000000c:174331001001.5 1acquired2e+03       softwaresoftware
119       FL26.1-80.4 33327c:144687WestonDateMyFamily.com02011-11-112013-01-012011-12-012011-12-010.05480.05480.06850.4   411e+05       2FL00001social0000000001c:1446870100001   0closed2.01e+03other_categoryother_category
1e+03       CA37.4-122   94304c:6592Palo AltoHyperic12004-01-012006-05-102007-06-052.36  3.43  3     5.34  429.9e+06 2CA10000software1000000000c:65920011002   1acquired2e+03       softwaresoftware
610       CA37.8-122   94104c:34545San FranciscoOptimal12008-01-012008-01-012013-01-220     5.06  5.01  5.79  1037.6e+06 2CA10000advertising0000100000c:345450011005   1acquired2.01e+03advertisingadvertising
246       CA34.4-120   93101c:17030Santa BarbaraSendMeHome.com02008-07-012012-06-042008-07-012008-07-010     0     0.737 0.737 215e+04       1CA10000games_video0000010000c:170300100002   0closed2.01e+03games_videogames_video
22       CA34  -118   90034c:10610Los AngelesGeodelic Systems02008-01-012011-01-012008-12-012010-09-230.918 2.73  2.42  2.73  831.05e+073CA10000mobile0010000000c:106101011002   1closed2.01e+03mobilemobile
1.01e+03CA34  -118   90401c:68470Santa MonicaBlockBeacon12012-01-012012-06-212012-06-210.471 0.471 0     0.918 1215e+05       2CA10000web0100000000c:684700100001   0acquired2.01e+03webweb
8       CA37.4-122   94041c:10197Mountain ViewPostPath12003-01-012004-12-072007-01-161.93  4.04  2     10.2   222.43e+073CA10000web0100000000c:101970001102.5 1acquired2e+03       webweb
595       CA37.4-122   95054c:33771Santa ClaraAttune Systems01999-01-012009-02-122006-06-272006-11-147.49  7.87  7.01  7.01  621.8e+07 1CA10000hardware0000000001c:337711001004   1closed2e+03       other_categoryother_category
757       CA37.8-122   94107c:437San FranciscoTokBox12007-05-012007-12-262010-11-150.655 3.55  3.84  6.56  2732.6e+07 5CA10000messaging0000000001c:4370011103.671acquired2.01e+03other_categoryother_category
336       MD39.2-76.8 Maryland 21045c:20062ColumbiaHeartscape12000-01-012009-10-152007-04-242007-04-247.32  7.32  5.01  5.01  611.7e+07 1MD00001biotech0000000100c:200620001001   1acquired2e+03       biotechother_category
493       CA37.4-122   94043c:281Mountain ViewPeerMe02004-01-012009-02-032005-01-012005-01-011     1     1.16  3.57  215e+06       2CA10000games_video0000010000c:2810010003   0closed2e+03       games_videogames_video
1.09e+03MA42.5-71.2 1803c:8251BurlingtonneoSaej02006-01-012013-06-012007-03-292010-12-211.24  4.97  1     1     151.31e+071MA00100web0100000000c:82511010002   1closed2.01e+03webweb
962       WA39.8-100   98104c:60243SeattleKiha Software02008-01-012011-08-012010-10-282010-10-282.82  2.82  0     2.82  112e+07       2WA00001software1000000000c:602430010001   0closed2.01e+03softwaresoftware
867       MA42.4-71.1 2138c:513CambridgeVlingo12006-06-012006-12-012009-09-160.501 3.3   2.07  7     1832.65e+074MA00100mobile0010000000c:5131011002   1acquired2.01e+03mobilemobile
876       TX30.3-97.7 78701c:51969AustinHurricane Party02010-05-012012-07-012010-05-012010-05-010     0     0.274 0.863 512e+04       2TX00010mobile0010000000c:519690100001   0closed2.01e+03mobilemobile
75       CA37.4-122   94085c:1284SunnyvaleMinekey02005-01-012012-08-182006-12-012007-08-011.92  2.58  2     6.92  1023.6e+06 3CA10000web0100000000c:12840110001   0closed2e+03       webweb
404       NY40.7-74   10012c:24029New YorkBlip12005-05-012006-03-012012-07-300.833 7.25  8.01  8.4   2372.73e+074NY01000games_video0000010000c:240290111112   1acquired2e+03       games_videogames_video
226       CA37.8-122   94105c:166772San FranciscoFabkids12012-01-012012-08-022012-08-020.586 0.586 1.05  1.05  812.6e+06 1CA10000ecommerce0000001000c:1667720010002   0acquired2.01e+03ecommerceecommerce
954       CA37.4-122   94306c:59709Palo AltoCafeBots02010-01-012010-10-012010-10-212010-10-210.803 0.803 0     1.41  515e+06       2CA10000web0100000000c:597090010001   1closed2.01e+03webweb
50       CA32.9-117   92121c:11888San DiegoAvaak12004-01-012008-10-032010-03-224.76  6.22  3.67  6.22  221.7e+07 2CA10000mobile0010000000c:118880011003.5 1acquired2e+03       mobilemobile
938       NY40.7-74   10011c:58550New YorkSavored12010-01-012010-01-012011-01-100     1.02  2.01  2.73  1223.75e+062NY01000hospitality0000000001c:585500110004   1acquired2.01e+03other_categoryother_category
698       CA37.8-122   94107c:4San FranciscoDigg12004-10-112005-10-012011-07-120.973 6.75  5.25  9.15  5744.5e+07 8CA10000news0000000001c:40011114.671acquired2e+03       other_categoryother_category
128       NY40.7-74   11101c:1475Long Island CitySongza12007-11-012011-09-192013-09-103.88  5.86  2.84  6.11  926.7e+06 4NY01000music0000000001c:14751000008   1acquired2.01e+03other_categoryother_category
386       CA37.5-122   94065c:23134Redwood CityBigfoot Networks12006-01-012006-03-062009-11-170.175 3.88  2     4.47  1232.08e+072CA10000hardware0000000001c:231341011002.331acquired2.01e+03other_categoryother_category
496       CA37.8-122   94104c:282San FranciscoKiptronic12005-05-012005-11-012008-06-050.504 3.1   2.24  3.76  1037.3e+06 3CA10000advertising0000100000c:2820111002   1acquired2e+03       advertisingadvertising
986       WA39.8-100   98104c:6340SeattleCozi Group02005-03-032013-01-312005-12-012012-12-270.748 7.82  4.32  5.9   1672.64e+073WA00001web0100000000c:63401011001.331closed2e+03       webweb
988       NY40.7-74   10011c:63621NYLifestander02010-09-012013-06-012010-10-022010-10-020.08490.08490     0     113.1e+04 1NY01000web0100000000c:636210100002   0closed2.01e+03webweb
425       CA37.5-122   94025c:251Menlo ParkJaxtr12005-10-012007-07-012008-06-231.75  2.73  1.75  6.15  1632.15e+074CA10000mobile0010000000c:2510011003.331acquired2e+03       mobilemobile
64       CO39.5-105   80112c:12285EnglewoodMX Logic12002-01-012006-11-072006-11-074.85  4.85  6.59  6.59  514e+06       1CO00001security0000000001c:122850000005   1acquired2e+03       other_categoryother_category
1.12e+03CA33  -117   90275c:885Solana BeachMetaplace12006-07-012007-01-012010-03-150.504 3.71  2.99  4.02  539.4e+06 4CA10000games_video0000010000c:8851011004   1acquired2.01e+03games_videogames_video
247       NY37.4-122   10004c:1704New YorkTravelMuse12007-04-162007-05-012009-06-010.04112.13  1.76  4.87  935.6e+06 4NY01000web0100000000c:17040011002   1acquired2.01e+03webweb
955       CA37.8-122   94105c:5986San FranciscoJambool12006-08-012008-08-012009-08-172     3.05  3.58  5.48  926e+06       2CA10000finance0000000001c:59860011002.5 1acquired2.01e+03other_categoryother_category
399       GA33.8-84.4 30309c:23756NW AtlantaZipcar12000-10-312002-12-202010-12-152.14  10.1   10.4   12.2   3546.07e+073GA00001transportation0000000001c:237561001012   1acquired2e+03       other_categoryother_category
745       CA37.8-122   94107c:43172San FranciscoHitpost12009-04-012010-01-012012-04-260.753 3.07  3.92  4.5   1632e+06       2CA10000sports0000000001c:431720100003.671acquired2.01e+03other_categoryother_category
345       CA37.8-122   94107c:20637San FranciscoHome-Account12008-11-012009-04-162009-07-160.455 0.704 0.581 1.74  521e+06       3CA10000finance0000000001c:206371010005.5 1acquired2.01e+03other_categoryother_category
335       PA40  -75.2 19004c:20033Bala CynwydPayParade Pictures02007-10-172012-01-272008-12-012009-03-131.13  1.41  0.792 1.4   322e+05       2PA00001games_video0000010000c:200330110002   1closed2.01e+03games_videogames_video
94       CA37.6-122   94066c:13504San BrunoPlanet Metrics02007-01-012011-02-072008-11-122008-11-121.87  1.87  0     1.86  212.3e+06 2CA10000cleantech0000000001c:135040010002   1closed2.01e+03other_categoryother_category
566       CA37.8-122   94108c:3185San Franciscokwiry02006-01-012009-04-232008-03-202008-03-202.22  2.22  0.748 3.42  511e+06       4CA10000mobile0010000000c:31850010001   1closed2.01e+03mobilemobile
1.03e+03CA37.8-122   94107c:725San Franciscoimeem12003-11-012004-09-012009-08-010.836 5.75  4.98  7.03  1352.48e+073CA10000music0000000001c:7251111002.4 1acquired2e+03       other_categoryother_category
107       IL42.1-87.7 60201c:13921EvanstonAmadesa02005-05-152013-07-012007-12-032011-10-052.55  6.39  6.64  6.64  1521.28e+071IL00001software1000000000c:139210011002   1closed2e+03       softwaresoftware
411       CA37.4-122   94043c:24549Mountain ViewCast Iron Systems12001-01-012005-03-282007-07-294.24  6.58  7     7     1023.05e+071CA10000enterprise0001000000c:245490000014.5 1acquired2e+03       enterpriseother_category
952       CA33.1-117   92010c:5952CarlsbadAptera02003-01-012011-12-012008-07-252011-07-135.57  8.53  5.61  7.84  333.63e+072CA10000automotive0000000001c:59521000101.5 1closed2e+03       other_categoryother_category
746       CA37.8-122   94111c:43183San FranciscoRentJuice12008-01-012010-03-042011-01-312.17  3.08  3.09  4.78  736.69e+063CA10000real_estate0000000001c:431831000001.671acquired2.01e+03other_categoryother_category
903       CA37.3-122   95014c:5485CupertinoParascale12005-01-012008-06-232008-06-233.48  3.48  3.68  5.63  811.14e+073CA10000network_hosting0000000001c:54850010002   1acquired2e+03       other_categoryother_category
1.12e+03CA34.1-118   90069c:9West HollywoodGeni12006-06-012007-01-012009-01-190.586 2.64  3.54  6.07  1331.65e+074CA10000web0100000000c:90011101.331acquired2.01e+03webweb
148       CA37.8-122   94111c:15129San FrancisoZentact02008-09-012012-01-012008-09-012008-09-010     0     3.41  3.41  312.5e+05 1CA10000network_hosting0000000001c:151290100003   0closed2.01e+03other_categoryother_category
597       NY40.7-74   10010c:339New YorkOutside.in12006-08-012007-02-012009-12-080.504 3.36  3.42  7.23  951.44e+075NY01000web0100000000c:3390111005.8 1acquired2.01e+03webweb
1.14e+03NY40.8-74   10001c:967New YorkSalesforce Buddy Media12007-09-012007-09-012011-08-150     3.96  4.76  5.15  2459e+07       3NY01000enterprise0001000000c:9671011113.8 1acquired2.01e+03enterpriseother_category
515       CA37.8-122   94017c:2925San FranciscoVizu Corporation12005-02-142006-02-202012-04-091.02  7.15  5.7   8.18  1041.31e+072CA10000advertising0000100000c:29250011004   1acquired2e+03       advertisingadvertising
1.11e+03CA37.4-122   94041c:86Mountain ViewZing Systems12007-06-012006-12-012007-01-01-0.499 -0.414 -0.499 5.77  1022.6e+07 4CA10000games_video0000010000c:860010102.5 1acquired2.01e+03games_videogames_video
1.02e+03MA42.5-71.2 1803c:69834BurlingtonDynamicOps12008-01-012011-02-282011-09-093.16  3.69  3     4.5   621.63e+072MA00100enterprise0001000000c:698340001002   1acquired2.01e+03enterpriseother_category
776       TX30.4-97.8 78759c:44434AustinMovero Technology12003-01-012013-06-012007-06-142010-03-234.45  7.23  7.01  7.01  525.99e+061TX00010enterprise0001000000c:444341010002   0acquired2e+03       enterpriseother_category
311       CA37.4-122   94303c:18897Palo AltoPunch Entertainment02005-05-102012-04-162006-02-272006-02-270.803 0.803 5.32  5.32  411.2e+06 1CA10000software1000000000c:188970010001   0closed2e+03       softwaresoftware
753       NY40.7-74   10003c:43416New YorkStickybits02009-01-012012-08-012010-03-092010-05-191.18  1.38  1.33  3.11  721.9e+06 2NY01000web0100000000c:434160110002.5 1closed2.01e+03webweb
398       CA37.8-122   94108c:23692San FranciscoEcast01999-01-012012-02-122008-05-072011-05-269.35  12.4   7.01  11.4   933.03e+072CA10000games_video0000010000c:236921000014.5 1closed2e+03       games_videogames_video
174       CA34  -118   90405c:1587Santa MonicaEdgeCast Networks12006-08-012006-08-012013-07-180     6.97  6.42  7.36  1957.4e+07 2CA10000network_hosting0000000001c:15870111111.751acquired2.01e+03other_categoryother_category
455       MI42.8-86   49464c:26390ZeelandRevetto02009-01-012009-05-182009-05-012009-05-010.329 0.329 -0.419 -0.419 312e+04       1MI00001web0100000000c:263900100001   0closed2.01e+03webweb
579       VA39  -77.4 20170c:32094HerndonZoomSafer12009-01-012009-03-012011-03-070.162 2.18  1.51  2.18  343.35e+062VA00001mobile0010000000c:320940111001.5 0acquired2.01e+03mobilemobile
1.12e+03CA37.4-122   94306c:8676Palo AltoBuysight12008-01-012008-11-042012-03-210.844 4.22  0.762 4.93  1832.4e+07 3CA10000advertising0000100000c:86760011003.671acquired2.01e+03advertisingadvertising
1.06e+03CA37.8-122   94110c:767San FranciscoTripIt12006-10-012007-04-012010-03-040.499 3.42  1.99  5.96  1431.31e+075CA10000travel0000000001c:7670101101.671acquired2.01e+03other_categoryother_category
959       NY40.8-74   10010c:6011New YorkPinch Media12008-04-012008-05-012010-01-060.08221.77  0.301 5.01  635.6e+05 5NY01000software1000000000c:60111100003.5 1acquired2.01e+03softwaresoftware
563       MN45  -93.3 55311c:31794MinneapolisEnstratius12009-01-012011-11-072011-11-072.85  2.85  2.91  4.19  713.5e+06 3MN00001enterprise0001000000c:317940010002   1acquired2.01e+03enterpriseother_category
1       MA42.4-71.1 2210c:10054BostonJumptap12005-01-012005-03-012012-07-020.162 7.5   7.05  8.62  4571.22e+083MA00100mobile0010000000c:100541011114.5 1acquired2e+03       mobilemobile
111       CA37.4-122   95134c:14036San JoseWiChorus12005-01-012005-12-222008-11-040.973 3.84  2     2     1844.25e+071CA10000mobile0010000000c:140361011102.5 1acquired2e+03       mobilemobile
664       NC36  -78.9 27713c:38123DurhamHatteras Networks12000-01-012005-06-082006-06-015.44  6.42  6.01  6.01  2623.6e+07 1NC00001software1000000000c:381231000013.5 1acquired2e+03       softwaresoftware
229       CA37.8-122   94111c:16709San FranciscoFocus02005-08-012012-09-152008-03-062008-03-062.6   2.6   2.92  5.48  711.22e+072CA10000enterprise0001000000c:167090000103   1closed2e+03       enterpriseother_category
820       NY40.7-74   10005c:46901New Yorkeasy2comply (Dynasec)12002-01-012007-10-022007-10-025.75  5.75  8.01  9.84  411e+06       2NY01000software1000000000c:469010010003   1acquired2e+03       softwaresoftware
86       WA30.6-87   98033c:13219KirklandClearwire12003-10-012008-05-062013-02-274.6   9.42  5.26  9.78  1945.7e+09 2WA00001mobile0010000000c:132190000004.251acquired2e+03       mobilemobile
780       TX33  -96.8 75001c:44576AddisonCREDANT Technologies12001-01-012007-12-202007-12-206.97  6.97  0.084912     615e+06       2TX00010security0000000001c:445760000105   1acquired2e+03       other_categoryother_category
905       NY40.8-74   10001c:55043New YorkExclusively.in12010-01-012010-11-032011-05-290.838 1.41  1.64  1.64  421.88e+071NY01000fashion0000000001c:550430011002.5 1acquired2.01e+03other_categoryother_category
739       MA42.5-71.2 1801c:42672WoburnOctavian02003-01-012011-02-012005-06-012007-10-102.42  4.78  4     4     221.5e+07 1MA00100software1000000000c:426720011002.5 1closed2e+03       softwaresoftware
78       NY40.8-74   10011c:130New YorkKickApps12004-03-012006-06-012008-11-252.25  4.74  5.34  7.27  2233.9e+07 5NY01000enterprise0001000000c:1300011103   1acquired2e+03       enterpriseother_category
958       MA42.4-71.1 2210c:60087BostonLocalocracy12009-01-012009-05-012011-02-040.329 2.09  1.33  2.75  431.72e+052MA00100web0100000000c:600870100001   0acquired2.01e+03webweb
418       NY40.7-74   10013c:24853New York CityPixable12009-03-122010-11-102011-04-221.67  2.11  2.3   3.55  2326.1e+06 2NY01000social0000000001c:248530011001   1acquired2.01e+03other_categoryother_category
124       CA37.9-122   94939c:14608LarkspurmFoundry12004-01-012006-03-212011-12-052.22  7.93  1.67  9.09  734.03e+075CA10000mobile0010000000c:146081001104   1acquired2e+03       mobilemobile
998       CA34.1-118   90046c:65389Los AngelesBevvy02011-01-082012-01-012011-05-202011-05-200.362 0.362 0.375 0.542 911e+05       3CA10000ecommerce0000001000c:653890100001   0closed2.01e+03ecommerceecommerce
281       WA47.6-122   98104c:1767SeattleLivemocha12007-09-012008-01-012013-02-250.334 5.49  2.75  5.59  1451.94e+072WA00001education0000000001c:17671011101.5 1acquired2.01e+03other_categoryother_category
960       CA37.6-122   94066c:6012San BrunoIronPort Systems12000-01-012002-06-252004-10-252.48  4.82  5.59  11.9   2126.15e+073CA10000hardware0000000001c:60120001014   1acquired2e+03       other_categoryother_category
784       CA37.8-122   94108c:44976San FranciscoCrowdcast12007-01-012010-06-102010-06-103.44  3.44  4     5.72  616e+06       2CA10000software1000000000c:449760010002   1acquired2.01e+03softwaresoftware
377       MA42.4-71.1 2114c:2275BostonWhere12004-01-012003-12-312009-01-01-0.00275.01  4.95  7.37  2341.91e+076MA00100mobile0010000000c:22750011102.5 1acquired2e+03       mobilemobile
222       NY40.8-74   10003c:16611New YorkPictela12008-10-172009-01-062010-11-060.222 2.05  0.04113.92  843.5e+06 3NY01000advertising0000100000c:166111010001.5 1acquired2.01e+03advertisingadvertising
1.15e+03CA37.5-122   94063c:975Redwood CityGrouply12006-03-012012-01-012007-06-012008-01-141.25  1.87  4.72  5.1   1332.6e+06 2CA10000network_hosting0000000001c:9750110003.671acquired2.01e+03other_categoryother_category
869       CA37.8-122   94103c:51332San FranciscoStorify12009-12-112009-07-012011-02-03-0.447 1.15  3.06  3.75  1432.02e+062CA10000web0100000000c:513320110001.331acquired2.01e+03webweb
630       CA34  -118   90404c:36151Santa MonicaShoeDazzle12009-03-012009-11-192012-10-030.721 3.59  2.84  4.02  1746.6e+07 4CA10000fashion0000000001c:361511011102.331acquired2.01e+03other_categoryother_category
134       NY40.7-74   10016c:148576New YorkLiftDNA12009-09-012011-02-012011-02-111.42  1.45  1.66  1.66  521e+06       1NY01000advertising0000100000c:1485760100003.5 0acquired2.01e+03advertisingadvertising
1.04e+03CA37.4-122   94306c:73586Palo AltoOnavo12010-01-012011-05-012012-01-241.33  2.06  3.25  3.78  1121.3e+07 2CA10000mobile0010000000c:735860011003   1acquired2.01e+03mobilemobile
806       MA42.4-71.2 2451c:46070WalthamPyxis Mobile01998-01-012012-08-012005-09-092012-01-107.69  14     12.5   14     332.42e+072MA00100software1000000000c:460701011002.331closed2e+03       softwaresoftware
57       MA42.4-71.2 2451c:12171WalthamGuardium12002-01-012005-08-122006-05-173.61  4.38  0     7.92  121.18e+072MA00100search0000000001c:121710000114.5 1acquired2e+03       other_categoryother_category
794       NV36  -115   89052c:45413HendersonTrooval02008-09-012011-02-012010-04-072010-11-051.6   2.18  0.08220.0822222.39e+061NV00001analytics0000000001c:454131000001   1closed2.01e+03other_categoryother_category
76       MA42.3-71.1 2116c:1285BostonCompete12000-01-012000-11-012007-08-010.836 7.59  11.6   13.6   3543.3e+07 5MA00100consulting0000000010c:12851011102.5 1acquired2e+03       consultingother_category
97       VA38.9-77.4 22102c:13730McLeanRollstream12005-01-012007-09-032008-11-182.67  3.88  4     7.32  427.5e+06 3VA00001software1000000000c:137300011001.5 1acquired2e+03       softwaresoftware
573       CA37.4-122   95134c:31936San JoseNeoGuide Systems12000-01-012006-09-292006-09-296.75  6.75  4     4     312.5e+07 1CA10000biotech0000000100c:319360000101   1acquired2e+03       biotechother_category
576       CA37.4-122   95054c:32011Santa ClaraAccept Software12002-01-012005-09-162010-12-143.71  8.96  4     4     742.53e+071CA10000software1000000000c:320111011102   1acquired2e+03       softwaresoftware
368       CA37.4-122   94301c:22203Palo AltoMilo12008-01-012008-11-012009-11-240.836 1.9   2.3   3.84  2124.95e+063CA10000web0100000000c:2220301100012.5 1acquired2.01e+03webweb
18       NY37.8-122   10003c:105New YorkSurphace12005-06-012005-04-012006-05-01-0.167 0.915 2.67  8.38  1523.5e+06 4NY01000web0100000000c:1050011005.5 1acquired2e+03       webweb
964       CA37.4-122   94041c:60436Mountain ViewCloudmeter12007-04-012012-04-272012-04-275.08  5.08  4.76  6.05  715e+06       2CA10000enterprise0001000000c:604360010001   0acquired2.01e+03enterpriseother_category
929       CA37.4-122   94010c:5779BurlingameZecter12007-06-012007-06-012009-12-140     2.54  3.77  5.92  932.52e+063CA10000network_hosting0000000001c:57791110001.671acquired2.01e+03other_categoryother_category
602       MA42.6-71.3 1851c:3413LowellDimdim12006-01-012007-02-012008-07-011.08  2.5   2.52  5.02  1028.4e+06 3MA00100web0100000000c:34130011002   1acquired2.01e+03webweb
966       CA34  -118   90405c:6049Santa MonicaTeleFlip02004-01-012008-01-012006-08-012008-01-012.58  4     2.03  4.62  524.9e+06 3CA10000mobile0010000000c:60490011001   1closed2e+03       mobilemobile
944       WA47.6-122   98004c:58998BellevueMessageGate02001-01-012012-07-162005-04-182005-04-184.3   4.3   5     5     315e+06       1WA00001software1000000000c:589981000005   1closed2e+03       softwaresoftware
360       CA37.8-122   94103c:21762San FranciscoZencoder12007-01-012010-02-012011-04-123.09  4.28  3.64  4.67  722e+06       2CA10000software1000000000c:217620110008.5 1acquired2.01e+03softwaresoftware
694       NY40.7-74   10010c:39801New YorkStorm Exchange02006-04-012009-03-122006-12-012008-03-040.668 1.93  0     0     221.08e+071NY01000enterprise0001000000c:398011010002   1closed2.01e+03enterpriseother_category
104       NY40.7-74   10003c:1388New YorkThe Huffington Post12005-05-092005-05-012010-08-01-0.02195.23  5.76  7.49  3153.7e+07 3NY01000news0000000001c:13881011102.5 1acquired2e+03       other_categoryother_category
40       CA37.4-122   94043c:11307Mountain ViewExaprotect12004-01-012006-07-102006-07-102.52  2.52  4     9.88  517.66e+063CA10000security0000000001c:113070010006   1acquired2e+03       other_categoryother_category
659       MA42.5-71.5 1460c:37929LittletonAkorri Networks12005-01-012005-05-052010-03-230.34  5.22  3     6.03  544.87e+073MA00100software1000000000c:379291011103   1acquired2e+03       softwaresoftware
824       CA34.1-118   90032c:47115Los AngelesGiiv02009-01-012012-08-012009-01-012010-06-010     1.41  1.41  1.41  123.35e+061CA10000messaging0000000001c:471150110002.5 1closed2.01e+03other_categoryother_category
49       CA34.1-118   91203c:11817GlendaleMyShape02003-09-012013-04-012007-07-172010-11-103.88  7.2   2.67  7.2   342.8e+07 2CA10000ecommerce0000001000c:118171001103   1closed2e+03       ecommerceecommerce
1.09e+03TX30.3-97.7 78701c:81476AustinBlackLocus12010-01-012011-07-012011-07-011.5   1.5   2.08  2.08  512.5e+06 1TX00010analytics0000000001c:814760010002   1acquired2.01e+03other_categoryother_category
156       IL41.9-87.6 60610c:155ChicagoFeedBurner12004-02-012004-06-012005-04-010.332 1.16  2.08  9.35  1628e+06       4IL00001web0100000000c:1550011004   1acquired2e+03       webweb
1.15e+03NY40.7-74   10011c:9822New YorkDailyBurn12007-10-012008-05-012009-05-260.584 1.65  0.633 4.26  625.4e+05 2NY01000web0100000000c:98220100002.5 1acquired2.01e+03webweb
1.13e+03CA37.8-122   94107c:93San FranciscoCastTV12006-01-012006-01-012007-04-010     1.25  1     5.44  423.1e+06 4CA10000games_video0000010000c:930110002   1acquired2.01e+03games_videogames_video
650       NY40.8-74   10001c:37635New YorkVenmo12009-04-042010-05-072011-08-011.09  2.33  2.83  4.69  821.2e+06 2NY01000mobile0010000000c:376350110006   1acquired2.01e+03mobilemobile
199       NY40.8-74   10017c:1627New YorkWeShow02007-06-012008-12-022007-06-012007-06-010     0     0.11  0.11  215e+06       1NY01000games_video0000010000c:16270010002   0closed2.01e+03games_videogames_video
151       CA37.8-122   CA 94105c:15294San FranciscoSenSage12004-08-182005-04-182012-01-010.666 7.38  2.37  2.37  663.71e+071CA10000security0000000001c:152941000113.8 1acquired2e+03       other_categoryother_category
474       MA42.5-71.3 1821c:27163BillericaLuminus Devices12002-01-012006-05-012013-03-014.33  11.2   8.7   8.71  341.36e+082MA00100other0000000001c:271630001014.331acquired2e+03       other_categoryother_category
1.07e+03NY40.7-74   10012c:77139New YorkBestVendor12011-01-012011-03-182012-02-010.208 1.08  0.162 2.65  344.2e+06 3NY01000software1000000000c:771390110003   1acquired2.01e+03softwaresoftware
1.08e+03CA37.2-122   95030c:80259Los GatosEyeona02011-01-012012-11-012011-10-102011-10-100.773 0.773 0.312 1.15  312e+06       2CA10000web0100000000c:802590000001   0closed2.01e+03webweb
464       CO39.9-105   80021c:26806BroomfieldColdSpark12001-01-012006-01-012006-01-015     5     5.5   5.5   316.5e+06 1CO00001software1000000000c:268061000001   1acquired2e+03       softwaresoftware
914       CA37.4-122   94040c:55592Mountain ViewWander (f. YongoPal)02010-01-012013-07-012010-04-012011-01-010.247 1     1.16  1.16  351.85e+051CA10000mobile0010000000c:555921100002   1closed2.01e+03mobilemobile
1.05e+03OR45.5-123   97214c:74928PortlandCrowdCompass12009-04-012011-12-112011-12-112.7   2.7   3.22  4     511.3e+06 2OR00001mobile0010000000c:749280010001   0acquired2.01e+03mobilemobile
583       MA42.4-71.1 2111c:32383BostonGoby12008-07-012010-10-202010-10-202.3   2.3   -0.334 2.36  412.5e+06 3MA00100search0000000001c:323830010002   1acquired2.01e+03other_categoryother_category
112       TX30.3-97.7 78701c:1419AustinFiveRuns12005-02-012005-09-012007-10-280.581 2.74  1.92  4.66  1129.2e+06 2TX00010web0100000000c:14190011001   1acquired2e+03       webweb
513       CO39.6-105   80111c:29168Greenwood VillageTrenStar12001-01-012007-04-062007-04-066.26  6.26  1     1     211e+07       1CO00001software1000000000c:291681000001   0acquired2e+03       softwaresoftware
963       WA47.6-122   98109c:60352SeattleWorld Blender02010-01-012011-02-012010-11-012010-11-010.833 0.833 0.666 0.666 311.2e+04 1WA00001games_video0000010000c:603520100001   1closed2.01e+03games_videogames_video
1.09e+03NY40.7-74   10003c:82843New YorkDispatch12011-05-012011-07-012011-11-100.167 0.529 0.167 2.44  429.83e+052NY01000messaging0000000001c:828430100006   1acquired2.01e+03other_categoryother_category
381       CA34.1-118   90015c:23052Los AngelesHauteLook12007-12-012009-05-122010-06-031.45  2.51  2.5   3.64  1524.1e+07 2CA10000fashion0000000001c:230520001101.5 1acquired2.01e+03other_categoryother_category
808       CA37.8-122   94103c:46129San FranciscoSponge12010-01-012010-04-192010-04-190.296 0.296 1.59  1.67  314e+05       2CA10000web0100000000c:461290100001   1acquired2.01e+03webweb
272       CA37.8-122   94110c:1760San FranciscoMogad12007-06-012007-08-012007-08-010.167 0.167 0.671 3.32  415e+05       2CA10000network_hosting0000000001c:17600010004   1acquired2.01e+03other_categoryother_category
257       CA37.4-122   94041c:173Mountain ViewMeebo12005-02-012005-10-012010-12-200.663 5.88  6.21  8.61  2957e+07       4CA10000web0100000000c:1730011112.8 1acquired2e+03       webweb
997       IL42  -88   60143c:6520ItascaAccertify12007-03-012008-06-032010-05-041.26  3.18  2.84  2.84  624.7e+06 1IL00001security0000000001c:65201010001   1acquired2.01e+03other_categoryother_category
252       MA37.1-95.7 2142c:1725CambridgeN2N Commerce12006-01-012008-01-012008-01-032008-01-032.01  2.01  0     0     113e+07       1MA00100ecommerce0000001000c:17251000002   1acquired2.01e+03ecommerceecommerce
448       MA42.4-71.2 2421c:26007LexingtonStreamBase Systems12003-01-012005-01-242012-05-182.07  9.38  7.01  7.01  1353.9e+07 1MA00100software1000000000c:260070001113.251acquired2e+03       softwaresoftware
194       CA37.4-122   95054-2913c:16189Santa ClaraProvigent12000-01-012006-06-072008-12-296.44  9     10     10     1033.2e+07 1CA10000semiconductor0000000001c:161890000013   1acquired2e+03       other_categoryother_category
799       CA33.7-118   92618c:45696IrvineIntegrien12001-01-012005-05-162010-05-114.37  9.36  4     9.36  532.45e+072CA10000enterprise0001000000c:456961011002.671acquired2e+03       enterpriseother_category
382       FL28  -82.5 33618c:23072TampaPersystent Technologies12002-01-012005-08-082009-12-033.6   7.93  8.59  9.11  132.15e+072FL00001software1000000000c:230720001114.5 1acquired2e+03       softwaresoftware
677       CA37.8-122   94110c:38794San FranciscoHello Chair02006-01-012013-07-012007-06-012010-04-121.41  4.28  1.33  5.18  528.9e+05 2CA10000mobile0010000000c:387941100003.5 1closed2.01e+03mobilemobile
933       CA37.6-122   94404c:58018Foster CityEncentuate12001-01-012005-03-222005-03-224.22  4.22  3     3     611.6e+07 1CA10000software1000000000c:580180001003   1acquired2e+03       softwaresoftware
1.13e+03CA37.8-122   94104c:921San FranciscoConsorte Media12005-07-012007-12-012007-12-012.42  2.42  2.5   8.4   517e+06       4CA10000web0100000000c:9210001002   1acquired2e+03       webweb
338       NY40.7-74   10011c:20146New YorkRightsFlow12007-10-012009-08-262009-08-261.9   1.9   1.9   4     1311.5e+06 3NY01000music0000000001c:201460010001   0acquired2.01e+03other_categoryother_category
1.04e+03WA47.6-122   98104c:7440SeattlethePlatform12000-01-012006-01-122006-01-126.04  6.04  10.5   12.6   1918e+06       4WA00001web0100000000c:74401000001   1acquired2e+03       webweb
864       CA34  -118   90401c:512Santa MonicaDocstoc12007-08-012007-11-012008-04-280.252 0.743 4.21  6.35  2224e+06       4CA10000web0100000000c:5120011003   1acquired2.01e+03webweb
337       CA37.5-122   94063c:20117Redwood CityZenprise12003-01-012005-06-062012-01-012.43  9.01  8.58  10     1066.46e+073CA10000mobile0010000000c:201171001103.671acquired2e+03       mobilemobile
14       CA40.8-74.4 94402c:10398San MateoPicateers02005-01-012011-11-012006-01-012008-08-251     3.65  3.5   3.5   1021.21e+071CA10000web0100000000c:103980011001   1closed2e+03       webweb
132       CA37.8-122   94111c:14854San FranciscoVontu12001-01-012005-03-212006-08-114.22  5.61  5     5     922e+07       1CA10000software1000000000c:148540000114.5 1acquired2e+03       softwaresoftware
651       TX30.4-97.8 78759c:37647AustinNextIO02003-01-012013-07-012005-01-112012-05-172.03  9.38  9.01  9.01  1044.96e+071TX00010hardware0000000001c:376470001102.671closed2e+03       other_categoryother_category
310       CA34.2-119   91302c:18875CalabasasEmergent Game Technologies12000-01-012007-07-052009-12-107.51  9.95  0.416 0.416 355.14e+071CA10000games_video0000010000c:188751000015.671acquired2e+03       games_videogames_video
482       CA37.8-122   94107c:27591San Franciscothreadsy12008-06-012008-03-272010-12-07-0.181 2.52  4.69  4.69  726.3e+06 1CA10000messaging0000000001c:275910011002   1acquired2.01e+03other_categoryother_category
1.06e+03NY40.8-74   10001c:76274New YorkSonar.me02010-01-012013-07-172012-01-012012-01-012     2     1.03  3.16  812e+05       3NY01000mobile0010000000c:762740100002   1closed2.01e+03mobilemobile
144       OH39.1-84.5 45202c:150577CincinnatiStyleZen02011-09-012013-04-012011-09-012011-09-010     0     0     0     212e+04       1OH00001fashion0000000001c:1505770100001   0closed2.01e+03other_categoryother_category
52       MA42.5-71.1 1864c:12052North ReadingKiva Systems12003-01-012003-01-012006-05-240     3.39  6.98  9.22  1321.16e+073MA00100hardware0000000001c:120520010102   1acquired2e+03       other_categoryother_category
564       CA37.4-122   94041c:3180Mountain ViewKrillion12006-05-012006-06-142006-06-140.12  0.12  -0.244 5.26  619.15e+062CA10000web0100000000c:31800010002   1acquired2.01e+03webweb
598       OH39.1-84.5 45202c:33912CincinnatiTransactiv02009-07-012013-07-192009-10-132009-10-130.285 0.285 0     0.285 211.2e+06 2OH00001advertising0000100000c:339120010004   1closed2.01e+03advertisingadvertising
1.03e+03CA34.1-118   90049c:71372Los Angelesnprogress02010-02-012012-01-012011-12-012011-12-011.83  1.83  1.16  1.16  411.7e+06 2CA10000social0000000001c:713720000007   1closed2.01e+03other_categoryother_category
814       CA39.8-105   94010c:465BurlingameBrightkite12007-01-012011-12-012007-08-012009-07-060.581 2.51  0.592 4.97  931.42e+064CA10000social0000000001c:4651100001   1acquired2.01e+03other_categoryother_category
262       CA37.8-122   94104c:17430San FranciscoPeanut Labs12005-01-012006-02-012008-02-191.08  3.13  5.92  7.93  1624.2e+06 2CA10000enterprise0001000000c:174300011001.5 1acquired2e+03       enterpriseother_category
789       MA42.4-71.1 2110c:4529BostonFlipKey12007-01-012007-12-012008-08-200.915 1.64  4.85  6.09  725e+05       2MA00100web0100000000c:45290110002   0acquired2.01e+03webweb
511       UT40.3-112   84042c:2889LindonFootnote12006-06-012006-06-162008-01-010.04111.59  2.28  4.39  421e+07       2UT00001web0100000000c:28890010002   0acquired2.01e+03webweb
805       CA34.1-118   90064c:46042Los AngelesNextMedium02004-01-012011-12-242005-02-012006-07-241.09  2.56  4     4     729.5e+06 1CA10000software1000000000c:460420011002.5 1closed2e+03       softwaresoftware
447       NJ40.3-74.1 7701c:25997Red BankKurani Interactive02000-01-012013-06-012010-11-252010-11-2510.9   10.9   9.25  9.25  512.75e+051NJ00001software1000000000c:259970100002   0closed2e+03       softwaresoftware
518       CA37.4-122   94306c:2953Palo AltoKapow Software12005-01-012005-02-012010-01-130.08495.04  1.83  1.83  1031.97e+071CA10000software1000000000c:29530001102.5 1acquired2e+03       softwaresoftware
849       MA42.4-71.1 2110c:49876BostonLocately12008-07-012010-08-012012-07-072.08  4.02  2.5   2.5   551.18e+061MA00100software1000000000c:498760100005   1acquired2.01e+03softwaresoftware
120       CA37.5-122   94306c:1447Palo AltoTrustedID12005-01-012005-10-012007-10-180.748 2.79  2.06  3.84  532.5e+07 2CA10000security0000000001c:14470011002   1acquired2e+03       other_categoryother_category
438       CA37.4-122   94086c:25688SunnyvaleAzingo02005-01-012009-08-112006-10-012008-07-181.75  3.55  2     2     428e+07       1CA10000mobile0010000000c:256880011001   0closed2e+03       mobilemobile
592       CA37.4-122   95051c:335Santa ClaraVudu12004-01-012005-06-012007-04-291.42  3.33  4.42  9.82  1123.6e+07 3CA10000hardware0000000001c:3350011003.5 1acquired2e+03       other_categoryother_category
468       CA37.4-122   94089c:27SunnyvalePlaxo12002-11-172002-11-012007-02-01-0.04384.21  6.42  9.07  2742.83e+074CA10000web0100000000c:270011112.5 1acquired2e+03       webweb
325       CA37.6-122   94303c:1957Palo AltoSharetivity02007-07-072012-11-112006-05-012006-05-01-1.18  -1.18  0.83  0.83  112e+06       1CA10000web0100000000c:19570000001   0closed2.01e+03webweb
981       CA37.6-122   94066c:63San BrunoYouTube12005-02-012005-11-012006-04-010.748 1.16  2.4   8.84  6321.15e+076CA10000games_video0000010000c:630011001   1acquired2e+03       games_videogames_video
942       NY40.7-74   10018c:58699New York CityHashable02010-01-012012-07-252010-11-222010-11-220.89  0.89  1.33  2.53  1514e+06       2NY01000mobile0010000000c:586990010003   1closed2.01e+03mobilemobile
752       NY40.7-74   10016c:43386New YorkMyNines02009-08-012011-08-052010-04-192010-04-190.715 0.715 0.748 2.01  215e+05       2NY01000ecommerce0000001000c:433860100001   1closed2.01e+03ecommerceecommerce
644       TX30.4-97.8 78759c:3717Austinitzbig02006-06-012010-03-242007-02-272007-02-270.743 0.743 1.17  3.92  914e+06       2TX00010search0000000001c:37170010002   1closed2.01e+03other_categoryother_category
1.02e+03NY40.7-73.9 11201c:70893BrooklynLoosecubes02010-01-012012-01-012010-01-012012-06-050     2.43  2.43  2.5   829.03e+062NY01000web0100000000c:708930110004   1closed2.01e+03webweb
197       CA34.1-118   90024c:162219Los AngelesContur02011-09-012012-11-012012-05-012012-05-010.666 0.666 0.419 0.419 212e+04       1CA10000messaging0000000001c:1622190100001   0closed2.01e+03other_categoryother_category
59       IN39.8-86.2 46204c:12178IndianapolisExactTarget12000-12-012004-07-212012-10-243.64  11.9   11     12.7   2972.38e+083IN00001software1000000000c:121781000002   1acquired2e+03       softwaresoftware
394       MA42.5-71.2 1803c:23487BurlingtonRhythmia Medical12004-01-012007-02-062010-09-243.1   6.73  4     6.73  331.47e+072MA00100medical0000000001c:234871001001   0acquired2e+03       other_categoryother_category
275       CA37.5-122   94403c:176278San MateoAdept Cloud12011-06-012012-10-012012-11-011.34  1.42  0.586 0.586 521.02e+061CA10000enterprise0001000000c:1762781010001   0acquired2.01e+03enterpriseother_category
366       CA37.4-122   94025c:22113Menlo ParkFactery02009-04-012013-01-172009-09-102009-09-100.444 0.444 0.819 0.819 211.2e+06 1CA10000web0100000000c:221131000002   1closed2.01e+03webweb
919       PA40.4-75   18938c:5617New HopeMeetMe, Inc.12005-04-012007-01-292008-07-291.83  3.33  3.27  7.63  1621.71e+074PA00001web0100000000c:56170011002.5 1acquired2e+03       webweb
180       CO39.6-105   80155c:15996EnglewoodWildBlue12004-01-012008-09-032008-09-034.68  4.68  5.97  5.97  015e+07       1CO00001web0100000000c:159961000004   1acquired2e+03       webweb
268       CA37.6-122   94401c:1753San Mateobluepulse01990-04-102010-01-012007-04-012007-04-0117     17     16.7   18.3   716e+06       2CA10000network_hosting0000000001c:17530010001   1closed1.99e+03other_categoryother_category
365       NY40.7-74   10003c:22057New YorkMr. Youth12002-01-012002-10-012009-02-010.748 7.09  8.01  9.87  521.51e+073NY01000advertising0000100000c:220570110001   0acquired2e+03       advertisingadvertising
627       CA38.2-123   94954c:35887PetalumaTeknovus12001-01-012002-01-012009-11-161     8.88  4     9.19  756.26e+072CA10000semiconductor0000000001c:358871011119.331acquired2e+03       other_categoryother_category
203       CA37.5-122   94063c:1628Redwood CityQik12006-06-012008-04-092011-01-061.86  4.6   3.92  6.43  1541.48e+073CA10000mobile0010000000c:16281001102.251acquired2.01e+03mobilemobile
779       CA34.2-118   91601c:4453North HollywoodEQAL12008-04-012008-04-162011-05-230.04113.14  1.85  4.49  3026.88e+065CA10000web0100000000c:44531010007   1acquired2.01e+03webweb
831       CA37.4-122   95054c:47689Santa ClaraAtrica02000-01-012007-12-132006-04-052006-04-056.26  6.26  6.01  6.01  1012.22e+071CA10000public_relations0000000001c:476890000009   1closed2e+03       other_categoryother_category
804       CO40  -105   80302c:459BoulderSocialthing12007-05-182007-08-012007-10-230.205 0.433 0.469 2.95  624.15e+052CO00001network_hosting0000000001c:4590100001   1acquired2.01e+03other_categoryother_category
545       NY40.7-74   10010c:3094New YorkNext New Networks12007-03-012007-01-012010-12-29-0.162 3.83  3     4.7   1642.71e+074NY01000web0100000000c:30940011103.5 1acquired2.01e+03webweb
68       CA34.4-120   93013c:12468CarpinteriaAdECN12003-01-012006-02-012006-02-013.09  3.09  5     5     613.1e+06 1CA10000advertising0000100000c:124680010005   1acquired2e+03       advertisingadvertising
1.11e+03CA37.5-122   94025c:856Menlo ParkCuil02005-01-012010-09-012007-03-012008-04-152.16  3.29  3.5   7.69  1323.3e+07 4CA00000search0000000001c:8560011002.5 1closed2e+03       other_categoryother_category
202       CA37.4-122   94043c:16276Mountain ViewSensory Networks12003-01-012005-10-102008-01-012.78  5     4.16  10.8   231.74e+072CA10000web0100000000c:162761000105   1acquired2e+03       webweb
710       CA37.5-122   94025c:410Menlo ParkFlock12005-01-012005-01-012008-05-210     3.39  5.4   8.71  1752.83e+074CA10000web0100000000c:4100111112   1acquired2e+03       webweb
1.04e+03CA37.6-122   94043c:726Mountain ViewAdMob12006-12-012006-09-012009-01-29-0.249 2.16  1.41  6.54  4244.68e+076CA10000advertising0000100000c:7260011102.5 1acquired2.01e+03advertisingadvertising
1.11e+03IL41.9-87.6 60654c:8573ChicagoFeeFighters12009-01-012010-05-012011-01-121.33  2.03  2     2.03  531.52e+062IL00001ecommerce0000001000c:85730100002.671acquired2.01e+03ecommerceecommerce
11       NY40.7-74   10010c:102867New York CityWeHostels12011-11-152012-03-182012-03-180.34  0.34  0.545 1.72  911.2e+06 3NY01000travel0000000001c:1028670100005   1acquired2.01e+03other_categoryother_category
741       CA37.4-122   94040c:431Mountain ViewTimeBridge12005-05-012005-07-052009-05-110.178 4.03  3.67  7.24  631.24e+074CA10000web0100000000c:4311011001.671acquired2e+03       webweb
761       CA37.8-122   94105c:43832San FranciscoLoyalty Lab12003-01-012005-03-222010-04-292.22  7.33  7.01  7.01  431.1e+07 1CA10000software1000000000c:438321101001.671acquired2e+03       softwaresoftware
1.09e+03TN36.2-86.8 37201c:83142NashvilleRentStuff.com12010-01-012011-05-052012-04-121.34  2.28  1     1     326.75e+051TN00001web0100000000c:831420100001.5 0acquired2.01e+03webweb
980       NY40.7-74   10012c:62802New YorkJumo12010-02-012010-11-012010-11-010.748 0.748 1.03  2.5   513.5e+06 2NY01000social0000000001c:628020000002   1acquired2.01e+03other_categoryother_category
921       MA42.5-71.3 1730c:56568BedfordSionex02001-01-012010-08-062005-12-072005-12-074.93  4.93  0     0     211.2e+07 1MA00100hardware0000000001c:565680000104   1closed2e+03       other_categoryother_category
885       CA37.5-122   94002c:531Belmontsezmi12007-01-012007-08-012011-11-070.581 4.85  0.907 5.42  1057.86e+074CA10000games_video0000010000c:5310011104.331acquired2.01e+03games_videogames_video
5       TN36.1-86.8 37212c:10158NashvilleStudioNow12007-01-012007-06-152013-01-290.452 6.08  3.74  3.74  231.53e+071TN00001photo_video0000000001c:101580010001   0acquired2.01e+03other_categoryother_category
43       CA37.8-122   94111c:11438San FranciscoPicApp12008-01-012008-09-172008-09-170.712 0.712 1.58  3     513.2e+06 3CA10000web0100000000c:114380010001   1acquired2.01e+03webweb
1.05e+03WA47.2-122   98371c:75796PuyallupMillion Dollar Earth02011-03-012012-10-012011-03-072011-03-070.01640.01640     0     113e+04       1WA00001advertising0000100000c:757960100002   0closed2.01e+03advertisingadvertising
796       CA37.5-122   94403c:45428San MateoComposite Software12002-01-012002-01-012012-10-240     10.8   9.59  9.59  2831.47e+071CA10000software1000000000c:454280100011   0acquired2e+03       softwaresoftware
210       CA37.8-122   94110c:16365San FranciscoTerracotta12003-01-012006-02-272008-09-013.16  5.67  9.01  9.01  922.35e+071CA10000software1000000000c:163651001005   1acquired2e+03       softwaresoftware
498       CA34  -118   90404c:2838Santa MonicaGenerate12004-01-012008-03-042009-07-144.18  5.54  6.38  6.38  028e+06       1CA10000games_video0000010000c:28380010001.5 1acquired2e+03       games_videogames_video
1.04e+03CA37.5-122   94401c:732San MateoAttributor12005-10-012006-01-282010-06-100.326 4.69  3.25  4.69  1342.52e+073CA10000software1000000000c:7320011114   1acquired2e+03       softwaresoftware
306       CA37.6-122   94403c:1853San MateoGreenplum Software12003-06-012006-03-012008-01-012.75  4.59  7.92  9.21  2146.1e+07 2CA10000software1000000000c:18530011103   1acquired2e+03       softwaresoftware
1.15e+03CA37.4-122   95054c:971Santa ClaraPlaySpan12006-05-012007-09-012010-08-191.34  4.3   2.08  5.84  1244.63e+074CA10000games_video0000010000c:9711011104.251acquired2.01e+03games_videogames_video
36       MD39  -77.1 20815c:1107Chevy ChaseJackBe12002-01-012006-01-102010-04-084.03  8.27  5.81  11.1   1542.45e+075MD00001software1000000000c:11070001114.331acquired2e+03       softwaresoftware
1.15e+03CA37.6-122   94304c:997Palo AltoZimbra12003-01-012006-04-012006-04-013.25  3.25  3.84  7.9   1911.45e+073CA10000enterprise0001000000c:9970000109   1acquired2e+03       enterpriseother_category
532       WA47.6-122   98005c:30307BellevueSmith & Tinker02007-01-012012-11-082009-08-252009-08-252.65  2.65  1     1     112.9e+07 1WA00001games_video0000010000c:303071000005   1closed2.01e+03games_videogames_video
200       CA37.4-122   94085c:16271SunnyvaleMu Dynamics12005-01-012005-01-012008-05-190     3.38  5.68  5.68  532.4e+07 1CA10000network_hosting0000000001c:162710011102.671acquired2e+03       other_categoryother_category
373       CA34.1-119   91302c:22712CalabasasFulcrum Microsystems12000-01-012005-05-092010-03-155.36  10.2   8.01  8.01  248.1e+07 1CA10000semiconductor0000000001c:227121000115.671acquired2e+03       other_categoryother_category
1.15e+03CA41.8-87.6 94105c:9782San FranciscoReTel Technologies12007-10-012009-08-062009-12-021.85  2.17  2.17  5.08  421e+06       3CA10000analytics0000000001c:97820100004.5 1acquired2.01e+03other_categoryother_category
1.01e+03CO40  -105   80027c:68169LouisvilleNexGen Storage12010-01-012011-02-072011-11-151.1   1.87  2.65  2.7   1421.2e+07 2CO00001software1000000000c:681691010002.5 1acquired2.01e+03softwaresoftware
269       CA37.5-122   94025c:17542Menlo ParkIntelliden12000-01-012005-12-212007-05-225.98  7.39  4     4     538e+07       1CA10000software1000000000c:175421000014   1acquired2e+03       softwaresoftware
773       CA37.3-122   95008-2069c:44268CampbellForrst12010-01-252011-03-242011-03-241.16  1.16  -0.06582.96  312.05e+053CA10000web0100000000c:442680100007   1acquired2.01e+03webweb
865       NY40.7-74   10017c:51228New YorkXGraph12008-10-012010-07-072010-07-071.76  1.76  0     3.08  513.75e+062NY01000analytics0000000001c:512280010001   1acquired2.01e+03other_categoryother_category
1.03e+03CA37.4-122   94301c:71852Palo AltoColor Labs Inc.02010-08-012013-06-012010-08-012011-03-230     0.641 1.58  3.07  1124.1e+07 2CA10000other0000000001c:718520011001.5 1closed2.01e+03other_categoryother_category
385       CA37.4-122   94306c:23125Palo AltoPlaydom12008-02-012009-11-112010-06-211.78  2.39  2.31  4.63  3727.6e+07 3CA10000games_video0000010000c:231250010004   1acquired2.01e+03games_videogames_video
658       MA42.5-71.5 1719c:37928BoxboroughDigital Reef12006-01-012006-01-012008-10-010     2.75  3.33  5.24  922e+07       2MA00100enterprise0001000000c:379280011001   1acquired2.01e+03enterpriseother_category
1e+03       CA37.8-122   94107c:65916San FranciscoServio12009-04-302010-08-132013-03-061.29  3.85  1.39  4.24  1129.36e+064CA10000analytics0000000001c:659160011001.5 1acquired2.01e+03other_categoryother_category
224       GA33.8-84.4 30309c:16618AtlantaVocalocity12007-01-012009-01-282011-08-292.08  4.66  4.58  4.73  921.36e+072GA00001software1000000000c:166180001103   1acquired2.01e+03softwaresoftware
153       CA37.8-122   94107c:1541San FranciscoDapper12006-10-012010-11-162007-12-012007-12-011.17  1.17  1.93  4.01  1913e+06       4CA10000advertising0000100000c:15410010002   1acquired2.01e+03advertisingadvertising
350       MA42.4-71.1 2139c:20889Cambridgeoneforty12009-03-312009-06-102010-01-110.195 0.784 1.21  2.38  1342.34e+063MA00100enterprise0001000000c:208890110005.751acquired2.01e+03enterpriseother_category
374       CA37.6-122   94401c:2272San MateoSmalltown02005-01-152010-01-042005-11-012005-11-010.794 0.794 2.05  3.33  714e+06       4CA10000web0100000000c:22720010001   0closed2e+03       webweb
856       CA37.4-122   94043c:5043Mountain ViewSkyrider02003-01-012008-10-152006-10-232008-03-053.81  5.18  1.75  3.59  221.7e+07 2CA10000software1000000000c:50431000103   1closed2e+03       softwaresoftware
729       NY40.8-74   10001c:42193New YorkSkillSlate12009-01-012010-10-202010-10-201.8   1.8   1.92  1.92  811.1e+06 1NY01000web0100000000c:421930100008   1acquired2.01e+03webweb
968       KY38  -84.5 40507c:60521LexingtonAwesomeTouch12010-07-262010-04-302011-06-01-0.238 0.849 0.901 0.901 345.97e+041KY00001software1000000000c:605210100001   1acquired2.01e+03softwaresoftware
839       CA37.8-122   94025c:4881Menlo ParkSyncplicity12008-11-032008-10-312008-10-31-0.0082-0.00822.97  3.7   1212.35e+063CA10000enterprise0001000000c:48810010002   1acquired2.01e+03enterpriseother_category
1.04e+03VA38.9-77.4 22031c:7345ChantillyFortisphere02006-01-012010-05-012007-11-192007-11-191.88  1.88  1     1     211e+07       1VA00001software1000000000c:73450010002   1closed2.01e+03softwaresoftware
12       CA37.4-122   94306c:103204Palo AltoPlayerDuel02011-01-012013-05-012011-09-052012-06-130.677 1.45  0     0     222.12e+041CA10000mobile0010000000c:1032041100001   1closed2.01e+03mobilemobile
441       MA42.4-71.3 2451c:25743WalthamAveksa12004-01-012006-06-142009-02-252.45  5.16  7.67  8.22  732.8e+07 2MA00100software1000000000c:257430011102.671acquired2e+03       softwaresoftware
458       CA37.4-122   95054c:26556Santa ClaraBeceem Communications12003-10-012005-06-302009-04-221.75  5.56  2.25  2.25  536.96e+071CA10000semiconductor0000000001c:265561001017.671acquired2e+03       other_categoryother_category
516       VA38.9-77.2 22102c:29312McLeanTrust Digital12003-03-012005-11-042009-07-292.68  6.42  2.84  7.24  1132.35e+072VA00001mobile0010000000c:293121001103.671acquired2e+03       mobilemobile
534       OR45.4-123   97035c:3050Lake OswegoSabrix12002-01-012006-06-212006-06-214.47  4.47  6.75  6.75  611.3e+07 1OR00001software1000000000c:30500000014   1acquired2e+03       softwaresoftware
471       NY40.7-74   10011c:2709New YorkPanther Express12005-01-012006-07-252008-02-271.56  3.16  3     3.5   822.18e+072NY01000games_video0000010000c:27091001002   1acquired2e+03       games_videogames_video
509       ME42.6-71.2 1876c:28752TewksburyBlueNote Networks12005-01-012005-09-262006-03-060.734 1.18  0.162 0.162 122.34e+071ME00001software1000000000c:287520011002.5 1acquired2e+03       softwaresoftware
44       CA37.5-122   94063c:1148Redwood CityPredictify02007-03-012009-08-012008-03-252008-03-251.07  1.07  0.838 3.99  414.3e+06 3CA10000advertising0000100000c:11480010002   1closed2.01e+03advertisingadvertising
472       CA37.4-122   95054c:27142Santa ClaraOptiMedica12004-01-012008-03-262013-05-104.24  9.36  5.01  5.01  1625.1e+07 1CA10000biotech0000000100c:271420000103.5 1acquired2e+03       biotechother_category
727       MA42.2-71.2 2026c:42123DedhamMetatomix12000-01-012003-09-082010-02-173.69  10.1   3     3     242.71e+071MA00100enterprise0001000000c:421231001004.671acquired2e+03       enterpriseother_category
720       CA37.3-122   95014c:41656CupertinoNeterion12001-01-012006-02-242006-02-245.15  5.15  4     4     616.48e+061CA10000public_relations0000000001c:416560000013   1acquired2e+03       other_categoryother_category
190       CA37.5-122   94085c:16145SunnyvaleSchooner Information Technology12007-05-012007-10-012009-07-240.419 2.23  2.23  4.34  823.5e+07 2CA10000enterprise0001000000c:161450011002.5 1acquired2.01e+03enterpriseother_category
160       GA34  -84   30043c:155821LawrencevilleNalace Corporation02012-01-012013-05-012012-04-192012-04-190.299 0.299 0.299 0.299 111.9e+04 1GA00001ecommerce0000001000c:1558210100001   0closed2.01e+03ecommerceecommerce
840       NJ40.7-74.1 7302c:49052Jersey CityQuidsi12005-01-012006-09-012010-04-201.67  5.3   5.84  8.35  2767.85e+073NJ00001ecommerce0000001000c:490520011113.4 1acquired2e+03       ecommerceecommerce
603       MD39  -76.5 21401c:34152AnnapolisNetcordia12000-01-012005-06-282006-07-315.49  6.58  6.75  6.75  321.3e+07 1MD00001network_hosting0000000001c:341520011001.5 1acquired2e+03       other_categoryother_category
530       CA37.4-122   94040c:3027Mountain ViewSearchMe02005-07-012009-10-212005-07-012008-05-010     2.84  2.92  4.31  754.36e+073CA10000search0000000001c:30270011113   1closed2e+03       other_categoryother_category
6       CA37.8-122   94103c:10176San FranciscoYammer12008-09-102009-01-192012-02-290.359 3.47  3.34  5.19  3851.42e+083CA10000enterprise0001000000c:101760011115.2 1acquired2.01e+03enterpriseother_category
851       CA37.4-122   94043c:50076Mountain ViewClever Sense12008-04-112010-06-172011-08-012.18  3.31  2.73  3.54  622e+06       2CA10000web0100000000c:500761010001.5 1acquired2.01e+03webweb
451       TX30.4-97.8 78730c:26122AustinAlterPoint12001-01-012003-01-012005-01-172     4.05  6     6     432.68e+071TX00010software1000000000c:261220011103   1acquired2e+03       softwaresoftware
265       CA37.3-122   95138c:17501San JoseShocking Technologies02006-01-012013-04-012007-04-172012-05-211.29  6.39  0     0     265.59e+071CA10000hardware0000000001c:175011011103.2 1closed2.01e+03other_categoryother_category
188       CA37.4-122   94040c:1613Mountain ViewRibbit12005-02-232006-10-012007-12-171.6   2.81  3.43  7.41  1421.1e+07 3CA10000mobile0010000000c:16130011002   1acquired2e+03       mobilemobile
719       CA37.4-122   95054c:41484Santa ClaraStorSimple12009-01-012009-06-012011-06-230.414 2.47  3     3     1933.15e+071CA10000enterprise0001000000c:414840011103.331acquired2.01e+03enterpriseother_category
1.05e+03DC38.9-77   20009c:76102WashingtonNationalField12009-06-122012-10-302012-10-303.39  3.39  -0.03014.43  411.5e+06 2DC00001enterprise0001000000c:761021000002   0acquired2.01e+03enterpriseother_category
1.06e+03NY40.7-74   10003c:76765New YorkTripl02011-05-172013-07-012011-05-202012-07-090.00821.15  -0.02191.23  539e+05       3NY01000social0000000001c:767650100001.5 1closed2.01e+03other_categoryother_category
423       CA37.3-122   95008c:24986CampbellSadra Medical12003-01-012004-06-172009-05-221.46  6.39  6.42  6.42  435.8e+07 1CA10000biotech0000000100c:249860011105   1acquired2e+03       biotechother_category
123       MA42.5-71.2 1803c:14593Burlingtonexpressor software12007-01-012007-07-012011-12-190.496 4.97  1     4.51  1042.9e+07 2MA00100software1000000000c:145931001002.671acquired2.01e+03softwaresoftware
100       NV36.2-115   89101c:138030Las VegasNSFW Corporation12011-01-012011-10-052013-06-140.759 2.45  2.16  2.9   322.5e+05 2NV00001news0000000001c:1380300100001.5 1acquired2.01e+03other_categoryother_category
990       CA37.8-122   94105c:63731San FranciscoWeatherista02010-08-162012-09-012010-08-152010-08-15-0.0027-0.00270.03560.0356215e+05       1CA10000web0100000000c:637310100001   0closed2.01e+03webweb
832       TX33  -96.7 75082c:47848RichardsonNavini Networks12000-01-012005-08-102006-06-215.61  6.47  4     4     323.09e+071TX00010public_relations0000000001c:478481000003.5 1acquired2e+03       other_categoryother_category
887       CA37.4-122   94089c:5347SunnyvaleVirtualLogix12002-01-012004-01-012010-01-122     8.04  6.59  6.59  942.93e+071CA10000software1000000000c:53471011102.671acquired2e+03       softwaresoftware
141       MA42.7-71.1 1810c:14993AndoverExit4101999-01-012013-05-012007-02-042011-05-128.1   12.4   11.8   12.1   1142.42e+072MA00100software1000000000c:149931010102.331closed2e+03       softwaresoftware
62       CA37.4-122   94024c:1223Los AltosSezWho12006-10-012007-10-012007-10-011     1     1.25  5.25  411e+06       3CA10000web0100000000c:12230010001   0acquired2.01e+03webweb
910       MN44.9-93.5 55343c:55421MinnetonkaJobs2Web12003-01-012004-01-012006-01-211     3.06  5.42  5.42  325.55e+061MN00001web0100000000c:554210110001   1acquired2e+03       webweb
499       CA37.4-122   94040c:28403Mountain ViewHighlightCam02009-07-272013-10-302009-06-012011-11-29-0.153 2.34  0.063 1.58  823e+06       3CA10000mobile0010000000c:284030110003.5 1closed2.01e+03mobilemobile
74       CA37.4-122   94040c:1283Mountain ViewMerchantCircle12005-10-012006-06-052007-09-010.677 1.92  4.98  6.65  1321.43e+073CA10000web0100000000c:12830011004.5 1acquired2e+03       webweb
146       CA37.4-122   94043c:15122Mountain ViewKace networks12003-01-012005-07-252006-05-222.56  3.39  8.15  8.15  721.1e+07 1CA10000software1000000000c:151221001001.5 1acquired2e+03       softwaresoftware
662       NY40.7-74   10014c:38019New YorkThwapr02007-01-012013-07-202009-01-012010-01-012     3     2.09  4.07  722e+06       3NY01000photo_video0000000001c:380191100003   0closed2.01e+03other_categoryother_category
844       CA40.2-112   94103c:4961San FranciscoZinch12007-02-012007-12-012009-10-200.83  2.72  4.25  4.79  1725e+06       2CA10000web0100000000c:49611100001   1acquired2.01e+03webweb
718       CA37.3-122   95014c:41483CupertinoCloud.com12008-01-012010-01-012010-01-012     2     3.66  4.08  1211.1e+07 2CA10000enterprise0001000000c:414830001003   1acquired2.01e+03enterpriseother_category
66       CA37.4-122   94063c:12348Redwood CityWildfire, a division of Google12008-07-012008-12-012011-12-010.419 3.42  3.6   4.85  1941.41e+074CA10000enterprise0001000000c:123480111002.251acquired2.01e+03enterpriseother_category
577       CA34.1-118   90036c:3202Los AngelesAuthenticlick02005-08-052009-01-012006-02-012006-02-010.493 0.493 2.24  2.24  815e+06       1CA10000search0000000001c:32020010001   0closed2e+03       other_categoryother_category
581       WA45.6-123   98665c:32144VancouverIdooble02009-01-012012-01-012009-01-012010-08-010     1.58  -0.167 -0.167 124e+05       1WA00001web0100000000c:321440100001   0closed2.01e+03webweb
578       CA37.7-122   94080c:32023South San FranciscoBioSeek12000-01-012007-05-232007-05-237.39  7.39  4     4     411e+07       1CA10000biotech0000000100c:320230000101   0acquired2e+03       biotechother_category
116       MA42.4-71.3 2451c:1445Walthamxkoto02005-01-012011-10-012005-11-012009-01-260.833 4.07  2     2     331.1e+07 1MA00100software1000000000c:14451001101.671closed2e+03       softwaresoftware
889       MA42.5-71.3 2421c:53686LexingtonCoradiant12000-01-012005-08-222005-08-225.64  5.64  8.01  11.3   911.27e+072MA00100public_relations0000000001c:536860000014   1acquired2e+03       other_categoryother_category
854       CA39.8-100   94566c:50208PleasantonQuantaLife12008-01-012010-12-132011-07-222.95  3.56  0     0     322.08e+071CA10000biotech0000000100c:502080001001   1acquired2.01e+03biotechother_category
238       CA37.4-122   95054c:16874Santa ClaraBroadLight12000-06-012005-11-172007-09-115.47  7.28  10.6   10.6   532.7e+07 1CA10000software1000000000c:168740000016   1acquired2e+03       softwaresoftware
991       NY40.7-74   10016c:643New YorkBBE12004-04-012008-01-012008-01-013.75  3.75  5.54  6.76  711e+07       3NY01000advertising0000100000c:6430010001   0acquired2e+03       advertisingadvertising
490       NY40.7-74   10013c:2804New YorkBoonty12001-03-012005-07-072005-07-074.35  4.35  6.17  9.09  711e+07       3NY01000games_video0000010000c:28040001004   1acquired2e+03       games_videogames_video
41       NY40.7-74   10010c:11397New YorkB-Side Entertainment02005-04-072010-03-012006-10-112008-11-141.51  3.61  1.32  4.16  827.35e+063NY01000games_video0000010000c:113970011004.5 1closed2e+03       games_videogames_video
717       CA37.3-122   95138c:41409San JoseTaggstr02009-07-012013-07-012010-04-072010-04-070.767 0.767 0     0     115e+04       1CA10000messaging0000000001c:414090100001   0closed2.01e+03other_categoryother_category
913       NY40.7-74   10010c:55436New YorkFashism02009-01-012013-09-272010-11-192010-11-191.88  1.88  1.66  3.02  511e+06       3NY01000fashion0000000001c:554360010007   1closed2.01e+03other_categoryother_category
70       CA37.4-122   94040c:12630Mountain ViewGoodmail Systems02003-01-012012-01-012005-10-172009-01-122.79  6.04  7.5   8.01  1644.5e+07 2CA10000security0000000001c:126300011102   1closed2e+03       other_categoryother_category
635       CA32.9-117   92121c:365San DiegoNirvanix02007-07-012013-10-152007-09-182012-05-030.216 4.84  0.216 6.25  2257e+07       5CA10000enterprise0001000000c:3651011104.2 1closed2.01e+03enterpriseother_category
348       WA47.6-122   98102c:20832SeattleLookStat02008-01-012012-05-292009-04-232009-04-231.31  1.31  1     1.31  315e+05       2WA00001ecommerce0000001000c:208320010001   1closed2.01e+03ecommerceecommerce
288       TX30.3-97.8 78746c:17809AustinLuminary Micro12004-01-012005-02-012007-08-231.09  3.64  3.5   3.5   234.4e+07 1TX00010semiconductor0000000001c:178090011104   1acquired2e+03       other_categoryother_category
400       CO39.6-105   80112c:23788EnglewoodZettaCore01999-01-012012-01-042009-05-112009-05-1110.4   10.4   5.84  5.84  412.1e+07 1CO00001semiconductor0000000001c:237881000005   1closed2e+03       other_categoryother_category
543       CA34.1-118   90038c:30834Los AngelesClicker12009-01-012009-09-152010-02-180.704 1.13  1.45  2.21  1221.9e+07 2CA10000games_video0000010000c:308340011003.5 1acquired2.01e+03games_videogames_video
850       CA37.6-122   94066c:49960San BrunoSocialShield12009-09-012010-10-052010-10-051.09  1.09  1.61  2.17  611e+07       2CA10000software1000000000c:499600010007   1acquired2.01e+03softwaresoftware
271       MA37.2-122   1752c:17581MarlboroughStorwize12004-01-012007-06-062008-04-023.43  4.25  6.01  6.42  1322.8e+07 2MA00100other0000000001c:175810001102   1acquired2e+03       other_categoryother_category
110       NH42.7-71.5 3062c:14028NashuaAutoVirt02007-01-012012-02-012007-01-012011-05-240     4.39  3.15  4.39  572.43e+072NH00001software1000000000c:140281111002   1closed2.01e+03softwaresoftware
82       CA37.4-122   94040c:1309Mountain ViewLoopt12005-01-012005-06-012010-05-030.414 5.34  5.52  7.19  2143.2e+07 3CA10000mobile0010000000c:13090111101.671acquired2e+03       mobilemobile
500       CA37.3-122   95014c:28420CupertinoBlue Lane Technologies12002-01-012005-02-012005-02-013.09  3.09  1     1     411.34e+071CA10000public_relations0000000001c:284200001002   1acquired2e+03       other_categoryother_category
1e+03       CA37.8-122   94107c:6562San FranciscoSocialcast12005-06-012009-04-062010-03-313.85  4.83  4.96  7.26  1839.4e+06 3CA10000enterprise0001000000c:65620111001.5 1acquired2e+03       enterpriseother_category
767       CO40  -105   80302c:4394BoulderCollective Intellect12005-01-012006-02-012012-12-071.08  7.94  3     7.43  1061.53e+073CO00001enterprise0001000000c:43941111002.5 1acquired2e+03       enterpriseother_category
878       WA47.6-122   98121c:52346SeattleWavii12009-03-012010-07-012010-07-011.33  1.33  2.37  4.16  312e+06       2WA00001web0100000000c:5234600000011   1acquired2.01e+03webweb
334       CA37.8-122   94103c:200San FranciscoSeesmic12007-06-012007-11-012011-02-010.419 3.67  0.893 5.28  2431.6e+07 4CA10000web0100000000c:2000011105.671acquired2.01e+03webweb
108       PA40  -75.2 19103c:139729PhiladelphiaMobileReactor02010-01-012013-07-012011-10-242012-06-151.81  2.45  0.748 0.748 221.18e+061PA00001software1000000000c:1397291000001   0closed2.01e+03softwaresoftware
282       CA37.7-122   94566c:17724PleasantonEchopass Corporation12000-01-012006-10-302010-04-076.83  10.3   13     13     2229e+06       1CA10000network_hosting0000000001c:177240000004   1acquired2e+03       other_categoryother_category
205       CA32.7-117   92128c:16285San DiegoID Analytics12002-01-012002-05-012007-05-160.329 5.37  9.01  9.01  933.52e+071CA10000web0100000000c:162850011103   1acquired2e+03       webweb
769       MA42.5-71.2 1803c:43954BurlingtonVela Systems12005-01-012006-05-012010-09-021.33  5.67  2.5   5.67  431.2e+07 2MA00100software1000000000c:439541011002.671acquired2e+03       softwaresoftware
481       CA37.4-122   94085c:27555SunnnyvaleFlowCardia12002-01-012007-08-302007-08-305.66  5.66  5     5     413e+07       1CA10000biotech0000000100c:275550000109   1acquired2e+03       biotechother_category
309       CA37.5-122   94403c:18804San MateoBizanga12003-01-012009-02-172009-02-176.13  6.13  7.17  7.17  518e+06       1CA10000security0000000001c:188040001002   1acquired2e+03       other_categoryother_category
129       CA37.8-122   94107c:14787San FranciscoTranspond12007-01-012009-02-042009-02-042.1   2.1   2.28  3.17  614.1e+06 3CA10000advertising0000100000c:147870010002   1acquired2.01e+03advertisingadvertising
1.09e+03IL40.1-88.2 61820c:81474ChampaignCaterva02008-01-012013-06-012009-12-152011-07-061.96  3.51  3.5   3.5   122.41e+061IL00001social0000000001c:814740100003   1closed2.01e+03other_categoryother_category
607       CA37.4-122   95054c:34401Santa ClaraInnovative Silicon02002-01-012011-01-012004-03-012007-11-062.16  5.85  6     6     347.2e+07 1CA10000other0000000001c:344010011102.251closed2e+03       other_categoryother_category
660       MN45  -93.3 55416c:37934Golden ValleyKardia Health Systems02006-01-012012-02-212007-01-012008-01-011     2     3.25  3.25  221.84e+071MN00001enterprise0001000000c:379341000001   0closed2.01e+03enterpriseother_category
433       NC35.7-79.2 27312c:25383PittsboroBiolex Therapeutics01997-01-012012-06-012005-01-072011-12-198.02  15     4     4     471.62e+081NC00001biotech0000000100c:253831001116.751closed2e+03       biotechother_category
848       MA42.4-71.1 2140c:49872CambridgeFoldrx Pharmaceuticals12003-01-012010-06-152010-06-157.46  7.46  5.59  5.59  712.9e+07 1MA00100biotech0000000100c:498721000007   1acquired2e+03       biotechother_category
1.06e+03MA42.4-71.1 2139c:7666CambridgeMetaCarta12001-01-012005-09-082005-09-084.69  4.69  4.16  9.27  1211e+07       2MA00100mobile0010000000c:76660000107   1acquired2e+03       mobilemobile
329       MA42.5-71.2 1803c:19670BurlingtonViridity Software12008-01-012008-12-012010-08-190.918 2.63  2.95  3.97  521.5e+07 2MA00100software1000000000c:196700011002   1acquired2.01e+03softwaresoftware
616       CA39.8-100   94025c:35148Menlo ParkDevtap02008-01-012009-02-252008-09-012008-09-010.668 0.668 0     0     212.6e+06 1CA10000search0000000001c:351480000001   0closed2.01e+03other_categoryother_category
113       CA37.8-122   94108c:142San FranciscoBebo12005-01-062006-05-012006-05-011.32  1.32  6.47  8.84  3011.5e+07 3CA10000web0100000000c:1420010001   1acquired2e+03       webweb
2       NY40.7-74   10001c:101312New YorkSideTour12011-06-012011-07-012013-03-250.08221.82  1.08  2.3   734e+06       2NY01000web0100000000c:1013120110002   1acquired2.01e+03webweb
809       CA37.7-122   94005c:46168BrisbaneSARcode Bioscience12006-01-012006-12-012011-07-180.915 5.55  5     5     927.3e+07 1CA10000biotech0000000100c:461681001003   1acquired2.01e+03biotechother_category
1.07e+03NY40.7-74   10013c:78868New YorkLore12011-03-012011-06-272012-04-050.323 1.1   0.841 2.04  541.21e+073NY01000education0000000001c:788680110004.671acquired2.01e+03other_categoryother_category
67       WA47.6-122   98101c:1236SeattlePelago12005-12-012006-11-012008-05-270.918 2.49  2.58  5.38  1832.24e+073WA00001mobile0010000000c:12361011003.331acquired2e+03       mobilemobile
599       CA37.8-122   94105c:33949San FranciscoDesk12009-01-012010-04-152011-01-041.28  2.01  2.16  3.44  1225.7e+06 3CA10000enterprise0001000000c:339490011004   1acquired2.01e+03enterpriseother_category
285       MA42.6-71.4 1886c:17774WestfordVirtual Computer12007-01-012007-12-012009-01-260.915 2.07  2     2     922.1e+07 1MA00100software1000000000c:177740011002.5 1acquired2.01e+03softwaresoftware
771       NC35.8-78.6 27518c:44064RaleighOasys Mobile01984-01-012012-05-212005-11-182005-11-1821.9   21.9   24.7   24.7   118e+06       1NC00001software1000000000c:440641000002   0closed1.98e+03softwaresoftware
974       CA37.4-122   94025c:6171Menlo ParkGamook02008-01-012010-01-012008-03-162008-03-160.205 0.205 0.164 0.164 111.5e+06 1CA10000games_video0000010000c:61710010001   1closed2.01e+03games_videogames_video
989       MA42.4-71.2 2453c:637WalthamQuattro Wireless12006-10-012007-05-012009-03-170.581 2.46  2.5   5.09  1732.83e+074MA00100advertising0000100000c:6370011101.671acquired2.01e+03advertisingadvertising
533       CA37.4-122   94301c:30343Palo AltoShopWell12008-01-012010-02-222012-12-202.15  4.97  2.37  2.71  457.94e+062CA10000web0100000000c:303431001002   1acquired2.01e+03webweb
633       MA42.6-71.3 1821c:36310BillericaNexx Systems12001-01-012005-09-292009-12-144.75  8.96  5     5     1031.52e+071MA00100semiconductor0000000001c:363100000111.5 1acquired2e+03       other_categoryother_category
1.1e+03 NY40.8-74   10003c:835NY5min Media12007-01-012007-04-012009-07-230.247 2.56  2     4.78  1131.28e+072NY01000games_video0000010000c:8350111001.5 1acquired2.01e+03games_videogames_video
817       IL41.9-87.6 60654c:46863ChicagoMyCabbage02010-03-012013-06-012011-03-242012-08-231.06  2.48  0     1.31  129.5e+05 2IL00001mobile0010000000c:468631010003   1closed2.01e+03mobilemobile
292       MA42.5-71.2 1801c:179WoburnGotuit12000-01-012002-12-012004-12-012.92  4.92  2     12.5   621.6e+07 5MA00100web0100000000c:1790011001   1acquired2e+03       webweb
237       CA37.3-122   95008c:16784CampbellTeleCIS Wireless12000-01-012006-01-012006-01-016.01  6.01  6.01  6.01  211e+07       1CA10000semiconductor0000000001c:167840000101   1acquired2e+03       other_categoryother_category
1.04e+03NY40.7-74   10013c:72750New YorkSnapette12011-01-012011-10-122011-10-120.778 0.778 0.34  2.49  511.5e+06 3NY01000fashion0000000001c:727500000001   0acquired2.01e+03other_categoryother_category
702       CA37.8-122   94107c:40152San FranciscoEmSense02004-01-012011-11-012009-11-032010-12-105.84  6.95  5.92  6.38  621.3e+07 2CA10000hardware0000000001c:401521000102   1closed2e+03       other_categoryother_category
896       NY40.7-73.9 11217c:54077BrooklynMakerBot12009-01-012011-08-232011-08-232.64  2.64  4.1   4.93  611e+07       2NY01000hardware0000000001c:540771000006   1acquired2.01e+03other_categoryother_category
17       NY42.7-73.2 10003c:10452New YorkImage Space Media12008-01-012010-01-192010-12-302.05  3     2     3.81  923.92e+062NY01000advertising0000100000c:104521010003   1acquired2.01e+03advertisingadvertising
911       NY40.7-73.9 11222c:55427BrooklynWanderfly12009-08-012009-08-012011-02-010     1.5   1.58  3.17  721.4e+06 2NY01000travel0000000001c:554270110006   1acquired2.01e+03other_categoryother_category
323       IL41.9-87.6 60654c:195311Chicagowalkby02012-08-012013-01-012012-08-012013-04-100     0.69  0     0.69  626.5e+05 2IL00001ecommerce0000001000c:1953111100001   1closed2.01e+03ecommerceecommerce
422       TX30.3-97.7 78702c:2497AustinFameCast02007-01-012010-01-012007-06-012010-03-300.414 3.24  0.414 6.8   539.7e+06 4TX00010games_video0000010000c:24971010001   1closed2.01e+03games_videogames_video
91       CA37.3-122   95110c:13465San JoseCassatt12003-01-012006-03-012006-03-013.16  3.16  2     2     611.5e+07 1CA10000software1000000000c:134650000013   1acquired2e+03       softwaresoftware
296       CA37.8-122   94608c:17983EmeryvilleVirtuOz12002-01-012005-10-102012-04-013.78  10.3   10     11     1843.88e+073CA10000enterprise0001000000c:179831011002   1acquired2e+03       enterpriseother_category
54       CA37.4-122   95112c:12099San JoseSolFocus02005-11-012013-01-012006-03-012012-04-010.329 6.42  1.17  4.99  682.11e+082CA10000cleantech0000000001c:120991011102.711closed2e+03       other_categoryother_category
866       CA37.4-122   94041c:51239Mountain ViewNimbula12008-01-012010-06-232010-08-232.48  2.64  3.42  5.2   822.08e+073CA10000enterprise0001000000c:512390011002   1acquired2.01e+03enterpriseother_category
1.05e+03CA37.8-122   94107c:74743San FranciscoGiftiki12009-06-012010-08-312011-04-201.25  1.88  2.25  3.22  421.02e+062CA10000social0000000001c:747430110002.5 1acquired2.01e+03other_categoryother_category
631       TX30.3-97.7 78730c:36192AustinStorspeed02007-01-012010-03-042007-06-072007-06-070.43  0.43  2     2     611.3e+07 1TX00010software1000000000c:361920010004   1closed2.01e+03softwaresoftware
341       NY40.7-74   10007c:20313New YorkSpaBooker12007-11-012008-01-012011-10-010.167 3.92  0     2.92  821.47e+072NY01000software1000000000c:203130110004   1acquired2.01e+03softwaresoftware
957       CA37.4-122   94043c:60Mountain ViewJajah12005-01-012006-03-012009-03-011.16  4.16  3     8.92  1943.3e+07 4CA10000mobile0010000000c:600011111.331acquired2e+03       mobilemobile
211       TX33  -96.7 75081c:1637RichardsonRipCode02006-08-062012-07-012006-11-012010-05-110.238 3.76  2.42  3.88  1043.3e+07 3TX00010software1000000000c:16370011104   1closed2.01e+03softwaresoftware
920       MA42.4-71.2 2452c:56478WalthamRippleFunction02010-03-012013-06-012010-05-012010-05-010.167 0.167 0.586 0.586 312e+04       1MA00100advertising0000100000c:564780100001   0closed2.01e+03advertisingadvertising
728       MA42.5-71.2 1803c:42163BurlingtonCerteon02003-01-012013-02-012007-07-162012-05-014.54  9.34  2     2     221.9e+07 1MA00100software1000000000c:421631001003.5 1closed2e+03       softwaresoftware
186       CA37.8-122   94104c:16111San FranciscoApplied Identity02002-01-012012-01-012005-01-132008-10-013.04  6.75  4     4     233.3e+07 1CA10000advertising0000100000c:161110011104   1closed2e+03       advertisingadvertising
407       GA34  -84.3 30350c:24274AtlantaPrenova12002-01-012006-05-102008-04-244.36  6.32  4     4     131.56e+071GA00001cleantech0000000001c:242741000001.331acquired2e+03       other_categoryother_category
1.06e+03CA37.8-122   92606c:763San FranciscoWooMe12000-12-012007-04-012008-06-126.33  7.53  7.17  10.9   831.74e+073CA10000web0100000000c:7630011002.331acquired2e+03       webweb
1.07e+03CA34.1-118   90028c:79089HollywoodHelpMeRent.com02010-10-012013-02-012011-08-012011-08-010.833 0.833 -0.167 1.19  511.54e+052CA10000real_estate0000000001c:790890100001   0closed2.01e+03other_categoryother_category
755       CA34.1-118   90301c:43480Los AngelesMail.com Media Corporation02004-01-012011-01-012008-10-212008-10-214.81  4.81  6.6   6.72  413.5e+07 2CA10000web0100000000c:434800000013   1closed2e+03       webweb
61       VA38.9-77.2 22182c:12224VienaDubMeNow02008-01-012013-06-012008-08-012012-06-050.584 4.43  1.25  2.15  547.52e+063VA00001mobile0010000000c:122241100001   0closed2.01e+03mobilemobile
900       TX30.4-97.8 78759c:54488AustinSmooth-Stone02008-01-012011-07-012010-08-162010-08-162.62  2.62  2.87  4.3   114.8e+07 3TX00010cleantech0000000001c:544881000005   1closed2.01e+03other_categoryother_category
193       CA37.3-122   95008c:16181CampbellONStor12000-01-012005-06-022008-04-185.42  8.3   8.01  8.01  636.58e+071CA10000network_hosting0000000001c:161811000014.671acquired2e+03       other_categoryother_category
259       NJ40.5-74.6 8844c:173118HillsboroughRelationship Analytics02012-08-012013-08-012013-04-052013-05-160.677 0.789 0     0     221.25e+051NJ00001analytics0000000001c:1731180100001   0closed2.01e+03other_categoryother_category
1.07e+03GA33.7-84.4 30305c:78759AtlantaJouleX12009-01-012011-06-102011-06-102.44  2.44  2.33  2.44  1011.7e+07 2GA00001enterprise0001000000c:787591000005   1acquired2.01e+03enterpriseother_category
624       CA37.5-122   94403c:3562San MateoEtelos01999-05-012013-01-012009-09-302012-05-2910.4   13.1   8.98  12.7   434.09e+063CA10000enterprise0001000000c:35621100001   0closed2e+03       enterpriseother_category
675       CA34.5-120   93105c:38655Santa BarbaraMake It Work01995-01-012012-06-012005-11-152005-11-1510.9   10.9   15.5   15.5   311e+06       1CA10000hardware0000000001c:386550010002   1closed2e+03       other_categoryother_category
880       TX30.3-97.7 78701c:52406AustinMapMyFitness12007-02-082007-01-012013-06-19-0.104 6.36  5.48  6.77  1352.35e+073TX00010health0000000001c:524061011101.751acquired2.01e+03other_categoryother_category
29       AZ33.4-112   85281c:10864TempeFetchBack12007-04-012008-01-012008-01-010.753 0.753 3.17  4.62  1311e+06       2AZ00001advertising0000100000c:108640010003   1acquired2.01e+03advertisingadvertising
1.14e+03MA42.4-71.1 2142c:934CambridgeSermo12006-01-012006-09-012011-02-170.666 5.13  2.75  6     1544.1e+07 2MA00100health0000000001c:9341011101.751acquired2.01e+03other_categoryother_category
436       MA42.4-71.1 2139c:25600CambridgeAlnara Pharmaceuticals12008-01-012008-10-302010-01-280.83  2.08  1     1     425.5e+07 1MA00100biotech0000000100c:256000011002   1acquired2.01e+03biotechother_category
821       CA37.8-122   60606c:46943ChicagoBraintree12007-10-012011-06-292012-09-173.75  4.97  4.68  4.84  1026.9e+07 2CA10000software1000000000c:469430011003.5 1acquired2.01e+03softwaresoftware
171       CA37.4-122   95035-5444c:15829MilpitasVirident Systems12006-01-012007-05-012013-01-281.33  7.08  4.87  7.01  2581.3e+08 3CA10000enterprise0001000000c:158291011113   1acquired2.01e+03enterpriseother_category
507       CA37.4-122   94041c:28483Mountain ViewLexity12009-08-012009-09-012011-03-030.08491.59  2.12  4     525.7e+06 3CA10000enterprise0001000000c:284830110004   1acquired2.01e+03enterpriseother_category
351       MA42.3-71.4 1702c:21040FraminghamDiligent Technologies12002-01-012007-08-212007-08-215.64  5.64  4.25  4.25  311.05e+071MA00100security0000000001c:210400000014   1acquired2e+03       other_categoryother_category
611       NY40.7-73.9 11211c:34549BrooklynHot Potato12009-01-012009-11-252009-11-250.899 0.899 0.414 1.63  1211.42e+063NY01000social0000000001c:3454900100016   1acquired2.01e+03other_categoryother_category
324       WA47.6-122   98119c:19538SeattleKashless02008-09-012010-12-252008-10-292011-02-040.159 2.43  -0.17  2.21  129e+06       2WA00001ecommerce0000001000c:195381010001   1closed2.01e+03ecommerceecommerce
130       CA37.4-122   94041c:148139Mountain ViewLaunchGram12012-01-102012-01-232012-10-010.03560.726 0.474 0.92  427e+04       2CA10000news0000000001c:1481390100001   1acquired2.01e+03other_categoryother_category
993       CA34  -118   90401c:64694Santa MonicaServiceMesh12008-01-012011-11-162011-11-163.88  3.88  3     5.83  911.5e+07 2CA10000enterprise0001000000c:646941000001   1acquired2.01e+03enterpriseother_category
318       CA37.8-122   94108c:1923San FranciscoLookery12007-08-012008-02-072008-09-040.52  1.1   0.252 2.06  1223.15e+062CA10000web0100000000c:192301100011.5 1acquired2.01e+03webweb
150       CA37.8-122   94109c:152560San FranciscoWantful02011-01-012013-09-062012-03-202012-03-201.22  1.22  1.42  2.68  615.5e+06 2CA10000ecommerce0000001000c:1525600010008   1closed2.01e+03ecommerceecommerce
1.03e+03CA38  -123   94903c:71639San RafaelZep Solar12009-01-012013-11-202013-11-204.89  4.89  3.29  3.29  811.06e+071CA10000cleantech0000000001c:716390010001   0acquired2.01e+03other_categoryother_category
395       CA37.9-122   94710c:2351BerkeleyMOG12005-06-012006-05-042010-02-260.923 4.74  0.671 7.77  1272.49e+073CA10000music0000000001c:23511110003   1acquired2e+03       other_categoryother_category
1.02e+03CA34.1-118   91105c:6854PasadenaLoud3r02007-09-012012-07-152009-06-052009-12-281.76  2.33  0.877 3.03  1223.53e+063CA10000web0100000000c:68541010001   0closed2.01e+03webweb
428       NY40.7-74   10011c:25306New YorkOyster.com12008-03-012008-03-012012-10-110     4.62  3.29  5.27  1542.34e+073NY01000travel0000000001c:253060011102.251acquired2.01e+03other_categoryother_category
33       CA37.4-122   95134c:10915San JoseLogLogic12002-01-012009-05-262009-05-267.4   7.4   7.4   11.9   1518.8e+06 3CA10000security0000000001c:109150000015   1acquired2e+03       other_categoryother_category
1.02e+03NY40.7-74   10012c:70661New YorkStyleTrek02010-02-012012-01-012010-02-012010-02-010     0     0.329 0.329 211.5e+06 1NY01000fashion0000000001c:706610000006   1closed2.01e+03other_categoryother_category
410       OR45.5-123   97201c:2434PortlandSnapNames12000-01-012001-06-012001-12-311.42  2     7.01  11.4   338.8e+06 2OR00001network_hosting0000000001c:24340011001   0acquired2e+03       other_categoryother_category
877       CA37.8-122   94107c:522San FranciscoSimple Star12001-01-012003-08-012005-08-102.58  4.61  0.581 10.2   327.1e+06 3CA10000web0100000000c:5220110001.5 1acquired2e+03       webweb
48       MA42.4-71.1 2142c:1165CambridgeStyleFeeder12006-05-032007-09-012009-05-011.33  3     2.16  5.96  833.5e+06 6MA00100ecommerce0000001000c:11651110001.671acquired2.01e+03ecommerceecommerce
1.08e+03CA37.4-122   94089c:80433SunnyvaleFlashSoft12009-11-252011-06-282011-06-281.59  1.59  1.19  2.55  613e+06       2CA10000software1000000000c:804330010002   1acquired2.01e+03softwaresoftware
1.08e+03NY43  -78.9 14217c:79456KenmoreTrustDegrees02011-03-012012-01-012011-04-172011-06-090.129 0.274 0.307 0.307 521.1e+04 1NY01000web0100000000c:794560100001   0closed2.01e+03webweb
256       CA33.6-118   92677c:17282Laguna NiguelSymwave12001-01-012007-07-182009-08-066.55  8.6   5     5     432.62e+071CA10000semiconductor0000000001c:172821000102.5 1acquired2e+03       other_categoryother_category
629       CA37.4-122   94043c:3610Mountain ViewClearwell Systems12004-12-062011-05-192006-04-042007-08-221.33  2.71  4.37  6.46  622.9e+07 3CA10000software1000000000c:36100001102.5 1acquired2e+03       softwaresoftware
946       CA32.8-117   92037c:59054La JollaNettle02010-10-042012-01-012011-08-112011-08-110.852 0.852 0     2.94  315e+05       3CA10000web0100000000c:590540100003   1closed2.01e+03webweb
375       CA37.5-122   94063c:22721Redwood CityCubeTree12008-01-012008-02-012009-11-020.08491.84  1.42  2.34  331.15e+073CA10000enterprise0001000000c:227210111001.5 1acquired2.01e+03enterpriseother_category
367       TX30.3-97.8 78703c:22168AustinInfochimps12009-07-142010-09-142013-06-041.17  3.89  2.3   3.43  855.35e+063TX00010enterprise0001000000c:221680110003   1acquired2.01e+03enterpriseother_category
51       CA37.8-122   94105c:1205San FranciscoSongbird02006-02-012013-06-282006-10-022010-01-270.666 3.99  5.08  7.37  2731.1e+07 4CA10000mobile0010000000c:12051010002   1closed2.01e+03mobilemobile
388       CA37.8-122   94103c:23139San FranciscoSimpleGeo12009-05-012009-11-102010-05-180.529 1.05  1.3   3.38  3039.81e+063CA10000advertising0000100000c:231390110008.671acquired2.01e+03advertisingadvertising
870       CA37.8-122   94110c:51379San Francisco1000memories12010-07-012010-01-012011-02-16-0.496 0.63  0.589 3.01  822.54e+062CA10000web0100000000c:513790110005   1acquired2.01e+03webweb
384       TX33  -96.8 75001c:23107AddisonSensorLogic12002-01-012007-06-192010-12-135.47  8.95  8.84  8.95  431.9e+07 2TX00010enterprise0001000000c:231071001105.331acquired2e+03       enterpriseother_category
853       CA37.4-122   94041c:50162Mountain ViewTouristEye12010-02-012010-02-012012-11-060     2.76  1.16  1.16  434.75e+051CA10000travel0000000001c:501620100004   0acquired2.01e+03other_categoryother_category
155       NY40.7-74   10005c:15470New YorkOberon Media12003-01-012008-10-062010-11-105.77  7.86  9.26  9.26  1623.6e+07 1NY01000games_video0000010000c:154701001001   1acquired2e+03       games_videogames_video
424       CA39.8-100   92130-2042c:25001San DiegoAragon Pharmaceuticals12009-01-012009-05-272012-10-040.4   3.76  3     3     1541.22e+081CA10000biotech0000000100c:250010011112.5 1acquired2.01e+03biotechother_category
208       NY40.7-74   10005c:163104New York#waywire12012-06-012012-06-302012-06-300.07950.07950.501 1.38  811.75e+062NY01000news0000000001c:1631040000005   1acquired2.01e+03other_categoryother_category
749       NY40.7-74   10003c:43263New YorkFeedtrace12009-08-102010-03-012010-03-010.556 0.556 -0.02471.93  311.3e+05 2NY01000web0100000000c:432630100001   0acquired2.01e+03webweb
60       IN39.9-86.1 46250c:12179IndianapolisVontoo02005-01-012012-10-312009-02-172011-02-244.13  6.15  5.57  6.11  1022.19e+063IN00001public_relations0000000001c:121791001003   0closed2e+03       other_categoryother_category
735       MA42.4-71.1 2142c:42501CambridgeAllurent12005-01-012010-02-222010-02-225.15  5.15  2     2     412e+06       1MA00100web0100000000c:425011000001   1acquired2e+03       webweb
142       CA37.5-122   94608c:15017EmeryvilleQuantivo12005-01-012008-01-092009-12-163.02  4.96  6.58  6.68  1129.4e+06 2CA10000analytics0000000001c:150170010002   1acquired2e+03       other_categoryother_category
250       CA25.8-80.3 94104c:1716San FranciscoScrapblog12006-01-012006-03-062010-02-050.175 4.1   0.734 5.05  841e+07       3CA10000web0100000000c:17160011101.251acquired2.01e+03webweb
987       CA37.6-122   94402c:6356San MateoYield Software12007-01-012008-06-042008-06-041.42  1.42  1     1     716e+06       1CA10000advertising0000100000c:63560001002   1acquired2.01e+03advertisingadvertising
1.03e+03PA40  -76.3 17603c:7163LancasterFlyCast02006-01-012013-01-012008-01-012009-07-222     3.56  4.57  4.57  322.1e+06 1PA00001mobile0010000000c:71631100002   0closed2.01e+03mobilemobile
816       WA39.8-100   98104c:46835SeattleOff & Away12009-12-012010-05-032010-10-210.419 0.888 0.08491.86  323.25e+063WA00001travel0000000001c:468351010001   1acquired2.01e+03other_categoryother_category
277       CA34.2-119   91360c:17634Thousand OaksNexsan12000-01-012003-12-012009-04-183.92  9.3   10.8   10.8   1022.45e+071CA10000hardware0000000001c:176341010002   1acquired2e+03       other_categoryother_category
826       UT40.2-112   84087c:47341ProvoTipping Bucket02009-04-082012-01-012009-04-012010-03-01-0.01920.896 1.06  1.06  427.2e+04 1UT00001enterprise0001000000c:473410100001   0closed2.01e+03enterpriseother_category
737       CA37.4-122   94304c:42610Palo AltoQlusters02001-01-012008-09-112007-08-082007-08-086.6   6.6   4     4     311.04e+071CA10000other0000000001c:426100000105   1closed2e+03       other_categoryother_category
3       NY40.8-74   10001c:10137New YorkProducteev12008-07-082008-07-152010-02-010.01921.57  2.48  4.87  1231.31e+062NY01000software1000000000c:101370100006   1acquired2.01e+03softwaresoftware
830       NY40.8-74   10036c:47662New YorkSpinTheCam02010-02-122012-02-172010-01-012010-01-01-0.115 -0.115 0.04660.0466111.5e+05 1NY01000games_video0000010000c:476620100001   0closed2.01e+03games_videogames_video
517       CA37.2-122   95032-5405c:29387Los GatosAmalfi Semiconductor12003-01-012006-02-012012-04-243.09  9.32  0.496 9.53  536.4e+07 2CA10000semiconductor0000000001c:293871001103.331acquired2e+03       other_categoryother_category
941       OH40  -83   43207c:58696ColumbusDormzy02010-05-012013-03-012010-05-012010-05-010     0     0     0     212.5e+05 1OH00001ecommerce0000001000c:586960100001   0closed2.01e+03ecommerceecommerce
101       CA34.1-118   91105c:13815PasadenaiChange12008-01-012007-10-012010-02-01-0.252 2.09  1.42  1.42  631.83e+061CA10000health0000000001c:138150110002   0acquired2.01e+03other_categoryother_category
908       OR39.8-100   97204c:55307PortlandAppFog12010-08-012011-01-012011-08-100.419 1.02  0.773 2.17  1029.8e+06 4OR00001enterprise0001000000c:553070011004.5 1acquired2.01e+03enterpriseother_category
342       CA38.9-77.1 94104c:2033San FranciscoHotPads12005-05-042007-03-012007-03-011.82  1.82  3.9   5.91  1512.3e+06 3CA10000web0100000000c:20330010001   0acquired2e+03       webweb
775       WA47.7-122   98052c:444RedmondSampa02005-03-012009-07-172007-08-012008-04-022.42  3.09  -0.162 3.97  321.31e+064WA00001web0100000000c:4440100001   0closed2e+03       webweb
793       CA37.8-122   94103c:454San FranciscoDanceJam02007-04-012011-01-012007-05-012008-02-010.08220.838 0     4.18  424.5e+06 5CA10000games_video0000010000c:4540101005.5 1closed2.01e+03games_videogames_video
47       CA37.6-122   94404c:11531Foster CityRight9012003-01-012005-02-282008-09-232.16  5.73  5     5     532.2e+07 1CA10000software1000000000c:115310011102.671acquired2e+03       softwaresoftware
1.04e+03CA37.8-122   94107c:741San FranciscoSocialMedia.com12007-01-012007-09-012009-01-290.666 2.08  3.03  4.29  2331e+07       3CA10000advertising0000100000c:7410111002.671acquired2.01e+03advertisingadvertising
657       NY40.7-74   10014c:37826New YorkBuyWithMe12009-03-012010-01-202011-06-010.89  2.25  2.66  2.75  2143.65e+073NY01000ecommerce0000001000c:378260011101.5 1acquired2.01e+03ecommerceecommerce
1.04e+03CO47.6-122   80205c:7299DenverPhotobucket12003-06-012005-03-012013-05-141.75  9.96  9.34  10.5   3573.37e+073CO00001web0100000000c:72991011002   1acquired2e+03       webweb
623       CA37.3-122   95014c:35579CupertinoXtremIO12009-01-012009-11-112011-12-050.86  2.93  3     3     431.9e+07 1CA10000enterprise0001000000c:355790011002   1acquired2.01e+03enterpriseother_category
359       CA37.4-122   94086c:21654SunnyvaleLevel 5 Networks12002-01-012005-06-202005-06-203.47  3.47  2     2     313e+07       1CA10000semiconductor0000000001c:216540001004   1acquired2e+03       other_categoryother_category
927       CA37.4-122   94041c:57338Mountain ViewVotizen12009-03-192010-09-232012-02-241.52  2.94  2.64  3.82  622.25e+062CA10000web0100000000c:573381000008.5 1acquired2.01e+03webweb
223       CA34.1-118   91006c:16613ArcadiaSiimpel Corporation12000-01-012005-11-112009-12-165.87  9.96  8.17  8.17  765.38e+071CA10000hardware0000000001c:166131000104.251acquired2e+03       other_categoryother_category
1.11e+03WA47.6-122   98006c:8527BellevueNapera Networks12006-12-012008-11-292008-11-292     2     -0.08223.52  316e+06       2WA00001network_hosting0000000001c:85270010001   1acquired2.01e+03other_categoryother_category
105       CA39.8-100   94063-2026c:1389Redwood CityNebuAd02006-01-012009-05-202007-07-012007-09-011.5   1.67  0     7.52  223.02e+073CA10000advertising0000100000c:13890011001.5 1closed2.01e+03advertisingadvertising
983       CA37.4-122   94085c:63053SunnyvalePasswordBank12008-01-012008-03-012009-07-010.164 1.5   3.16  5.55  623.5e+06 2CA10000software1000000000c:630530110001   0acquired2.01e+03softwaresoftware
1.01e+03CA37.4-122   94306c:668Palo AltoSnapTell12006-01-012007-06-072007-06-071.43  1.43  2.35  3.46  514e+06       3CA10000software1000000000c:6680010004   1acquired2.01e+03softwaresoftware
248       CA37.4-122   94089c:17070SunnyvaleCloudShield Technologies12000-01-012005-10-282007-09-175.83  7.72  10     10     1122.5e+07 1CA10000software1000000000c:170701000004.5 1acquired2e+03       softwaresoftware
1.04e+03NY40.7-74   10011c:7329New YorkInstinctiv12007-08-012008-06-012011-05-050.836 3.76  0.904 0.904 531.42e+061NY01000mobile0010000000c:73291100002   1acquired2.01e+03mobilemobile
584       CA37.4-122   94301c:32475Palo AltoWaze12007-01-012008-03-012011-10-181.16  4.8   2.33  6.9   1836.7e+07 5CA10000transportation0000000001c:324750011102.671acquired2.01e+03other_categoryother_category
916       CA37.5-122   94070c:5585San CarlosAster Data Systems12005-07-012005-11-012010-09-220.337 5.23  4.17  5.72  1345.3e+07 3CA10000analytics0000000001c:55850111104.5 1acquired2e+03       other_categoryother_category
949       CA34.1-118   90024c:59298Los AngelesDiversion02010-05-012012-06-012010-10-182011-07-220.466 1.22  0     1.22  523e+05       2CA10000games_video0000010000c:592980101002   1closed2.01e+03games_videogames_video
331       CA37.4-122   94301c:19725Palo AltoCodesion12002-01-012007-09-012010-07-015.67  8.5   6.75  8.09  431.4e+06 2CA10000software1000000000c:197250100001   0acquired2e+03       softwaresoftware
652       CA37.8-122   94110c:3770San FranciscoXoopit12004-01-012006-12-012008-04-022.92  4.25  2     7.17  426.5e+06 3CA10000web0100000000c:37700010007   1acquired2e+03       webweb
83       CA37.8-122   941017c:13127San FranciscoOne Block Off the Grid (1BOG)12008-11-012010-02-112010-02-111.28  1.28  2.7   3.58  815e+06       3CA10000cleantech0000000001c:131270010001   1acquired2.01e+03other_categoryother_category
947       WA39.8-100   98104c:59187SeattleAppature12007-01-012009-12-072012-07-132.93  5.53  3.92  6.2   629.6e+06 2WA00001enterprise0001000000c:591870010003   1acquired2.01e+03enterpriseother_category
427       WA47.6-122   98005c:253BellevueAction Engine12000-02-012000-05-012007-07-010.247 7.42  3.92  10.9   955.82e+073WA00001mobile0010000000c:2530011111.4 1acquired2e+03       mobilemobile
93       MA42.5-71.4 1720c:1350ActonBlackwave12006-01-012006-12-012009-09-300.915 3.75  0.581 4.88  1432.8e+07 2MA00100network_hosting0000000001c:13500011102.671acquired2.01e+03other_categoryother_category
453       TX33  -96.8 75244c:26240DallasSoftLayer12005-01-012009-09-302010-03-254.75  5.23  5.85  7.76  1023e+07       3TX00010network_hosting0000000001c:262401000001   0acquired2e+03       other_categoryother_category
614       CA34  -118   94301c:3487Palo AltoMytopia12007-01-012008-01-012009-03-011     2.16  4.36  5.33  1023.5e+06 2CA10000games_video0000010000c:34870110002   0acquired2.01e+03games_videogames_video
874       CA37.4-122   94085c:51890SunnyvaleBARRX Medical12003-01-012010-07-142010-07-147.54  7.54  7.01  7.01  611.5e+07 1CA10000medical0000000001c:518900000016   1acquired2e+03       other_categoryother_category
131       OH41.7-83.5 43607c:148284ToledoClassiphix02009-09-192013-05-012011-01-012011-01-011.28  1.28  0     0     111.5e+04 1OH00001ecommerce0000001000c:1482840100001   0closed2.01e+03ecommerceecommerce
663       WA47.6-122   98101c:38095SeattleStartupDigest12009-11-162011-03-092011-03-091.31  1.31  1.31  2.88  1112e+05       3WA00001news0000000001c:380951000001   0acquired2.01e+03other_categoryother_category
711       CA37.8-122   94111c:41006San FranciscoCohuman12009-10-092009-09-092011-01-01-0.08221.23  0.315 1.3   421.4e+06 2CA10000enterprise0001000000c:410060100003   0acquired2.01e+03enterpriseother_category
488       NY40.7-74   10038c:27938New YorkCorrelix02006-01-012013-05-012005-02-192012-02-14-0.866 6.12  5     5     541.14e+071NY01000enterprise0001000000c:279381001003   1closed2.01e+03enterpriseother_category
932       TX30.3-97.7 78701c:5801AustinOtherInbox12008-01-012008-01-012010-09-200     2.72  1     5.95  443.8e+06 4TX00010messaging0000000001c:58010110004.751acquired2.01e+03other_categoryother_category
283       CA37.6-122   94404c:17738San MateoM-Factor12003-01-012007-06-142009-02-104.45  6.12  6.59  6.59  321.01e+071CA10000software1000000000c:177381000103   1acquired2e+03       softwaresoftware
376       CA37.6-122   94403c:22726San MateoServo Software12008-01-012009-12-152009-12-151.96  1.96  1.96  2     1113.01e+063CA10000software1000000000c:227260001001   1acquired2.01e+03softwaresoftware
754       CA37.6-122   94402c:43458San MateoLevanta01998-01-012008-05-092007-09-232007-09-239.73  9.73  6     6     218e+06       1CA10000software1000000000c:434581000003   1closed2e+03       softwaresoftware
322       CA37.6-122   94401c:195233San MateoEdgeSpring12010-07-012010-07-012013-05-170     2.88  2.34  2.34  1521.27e+071CA10000analytics0000000001c:1952330010001.5 1acquired2.01e+03other_categoryother_category
976       CA33.8-118   90501c:6219TorranceDotSpots02007-09-012012-04-152007-09-012007-09-010     0     0.334 3.22  513e+05       4CA10000public_relations0000000001c:62190100002   0closed2.01e+03other_categoryother_category
346       CA33.6-112   90291c:20672Santa MonicaRepublic Project12008-08-012012-09-012012-09-014.09  4.09  4.67  5.19  1311e+06       2CA10000advertising0000100000c:206720100005   1acquired2.01e+03advertisingadvertising
781       CT39.4-84.2 6880c:44616WestportYamisee02010-01-012013-07-012010-03-242010-12-150.225 0.953 0.581 1.07  227e+05       2CT00001web0100000000c:446160100002.5 0closed2.01e+03webweb
969       WA47.6-122   98109c:60580SeattleThinkfuse12010-08-012010-11-012011-03-240.252 0.644 1.27  1.75  625.32e+052WA00001enterprise0001000000c:605800100005   1acquired2.01e+03enterpriseother_category
37       CA37.4-122   94301c:1111Palo AltoEchoSign12005-07-152005-10-012007-10-010.214 2.21  4.63  5.55  828.5e+06 3CA10000web0100000000c:11110011001   1acquired2e+03       webweb
519       WA47.6-122   98104c:2955SeattlePI Corporation12003-01-012006-07-272006-07-273.57  3.57  5.88  9.38  219.4e+06 3WA00001network_hosting0000000001c:29550001001   1acquired2e+03       other_categoryother_category
133       RI41.8-71.4 2903c:148566ProvidenceMoveableCode, Inc.02010-01-012012-01-142009-01-012012-04-01-1     2.25  1.75  1.75  323.5e+05 1RI00001mobile0010000000c:1485660100001   1closed2.01e+03mobilemobile
1.02e+03NY40.6-73.9 10013c:703New YorkDaylife12006-04-012007-06-012009-06-161.17  3.21  0.753 2.81  1621.23e+073NY01000enterprise0001000000c:7030001101.5 1acquired2.01e+03enterpriseother_category
676       MA42.6-71.4 1824c:38721ChelmsfordDesktone12006-01-012007-07-302011-12-161.58  5.96  4.42  4.42  652.54e+071MA00100network_hosting0000000001c:387211011003   1acquired2.01e+03other_categoryother_category
1.07e+03CA37.8-122   94105c:79431San FranciscoPulse12010-05-012010-10-062011-06-160.433 1.13  2.69  3.54  2329.8e+06 2CA10000news0000000001c:794310110004.5 1acquired2.01e+03other_categoryother_category
857       CA37.8-122   94107c:50449San FranciscoOpzi02010-05-012013-07-012010-01-012010-09-01-0.329 0.337 0.408 0.871 521.02e+062CA10000games_video0000010000c:504490100005   1closed2.01e+03games_videogames_video
975       CO40  -105   80302c:61783BoulderStanding Cloud12009-01-012009-01-012012-06-210     3.47  0     1.91  451e+07       2CO00001enterprise0001000000c:617831011001.5 1acquired2.01e+03enterpriseother_category
9       IL41.9-87.7 60647c:10199ChicagoWhere I've Been12007-06-082008-03-152010-04-150.77  2.85  -0.433 2.85  321.75e+062IL00001travel0000000001c:101991100001   1acquired2.01e+03other_categoryother_category
648       CA37.8-122   94103c:37304San FranciscoHipChat12009-09-012010-08-102010-08-100.94  0.94  1.5   3.82  411e+05       2CA10000messaging0000000001c:373040100003   1acquired2.01e+03other_categoryother_category
294       CA37.4-122   94301c:179507Palo AltoScaleIO12011-01-012012-12-042012-12-041.93  1.93  1.67  2.47  111.2e+07 2CA10000software1000000000c:1795071000002   1acquired2.01e+03softwaresoftware
907       NY40.7-74   10010c:55122New YorkGroupMe12010-05-012010-08-252011-01-040.318 0.679 0.794 2.85  1621.14e+073NY01000messaging0000000001c:551220101008.5 1acquired2.01e+03other_categoryother_category
189       CA37.4-122   95054c:16134Santa ClaraKickfire02006-01-012010-06-172008-07-312008-07-312.58  2.58  3     4.61  412e+07       2CA10000software1000000000c:161340001004   1closed2.01e+03softwaresoftware
622       TX30.3-97.8 78746c:35511AustinLifeSize, a Division of Logitech12003-01-012005-12-192006-09-182.97  3.72  6.97  8.33  1624.25e+073TX00010public_relations0000000001c:355110000115.5 1acquired2e+03       other_categoryother_category
528       CA33.9-118   CA 90245c:30152El Segundo,CHiL Semiconductor12006-01-012006-01-012008-05-070     2.35  0     5.16  732.25e+072CA10000semiconductor0000000001c:301521001102.331acquired2.01e+03other_categoryother_category
435       NJ40.7-75   8827c:25510HamptonEnpirion12001-01-012004-12-212011-03-313.97  10.2   3     3     845.9e+07 1NJ00001semiconductor0000000001c:255100001106   1acquired2e+03       other_categoryother_category
594       ID43.5-112   83402c:33519Idaho FallsRFinity02008-10-012013-06-012011-02-012011-02-012.34  2.34  0.581 2.37  514e+06       4ID00001mobile0010000000c:335190010001   1closed2.01e+03mobilemobile
730       CA32.9-117   92121c:42223San DiegoecoATM12008-08-022010-02-172013-02-061.55  4.52  1.66  4.92  647.14e+073CA10000cleantech0000000001c:422231010002.671acquired2.01e+03other_categoryother_category
734       CA37.8-122   94103c:42497San FranciscoAdura Technologies12008-01-012008-10-162012-04-260.792 4.32  3.98  3.98  532.55e+071CA10000cleantech0000000001c:424970011002.671acquired2.01e+03other_categoryother_category
147       CA39.8-100   94040-2573c:15123Mountain ViewRhythm NewMedia12005-01-012010-11-102012-09-115.86  7.7   5.86  7.67  2842.89e+073CA10000advertising0000100000c:151231000102.671acquired2e+03       advertisingadvertising
397       CA37.8-122   94105c:23588San FranciscoTopsy Labs12007-01-152008-01-012012-10-010.962 5.72  6.04  6.88  1863.52e+073CA10000analytics0000000001c:235881011102.331acquired2.01e+03other_categoryother_category
667       MA42.5-71.2 1803c:38273BurlingtonDigit Wireless02000-01-012012-01-012005-03-142008-02-115.2   8.12  8.01  8.01  221e+07       1MA00100public_relations0000000001c:382731000102.5 1closed2e+03       other_categoryother_category
143       CA37.4-122   94025c:15018Menlo ParkSilver Tail Systems12008-01-082008-09-262011-09-220.718 3.71  0.537 3.63  1132.21e+074CA10000analytics0000000001c:150181011002.671acquired2.01e+03other_categoryother_category
649       MA42.5-71.4 1720c:37335ActonTatara Systems12001-01-012004-01-202010-06-223.05  9.48  1     1     453.3e+07 1MA00100mobile0010000000c:373351001112   1acquired2e+03       mobilemobile
558       CA37.4-122   94303c:31559Mountain ViewReliant Technologies12001-01-012007-04-192007-04-196.3   6.3   6     6     911.5e+07 1CA10000biotech0000000100c:315590000003   1acquired2e+03       biotechother_category
1.14e+03CA37.3-122   95008c:9665CampbellAtrua Technologies12000-01-012006-12-072009-02-256.94  9.16  6.01  6.01  631.3e+07 1CA10000mobile0010000000c:96650000013   1acquired2e+03       mobilemobile
302       CA37.3-122   95008c:18163CampbellCasabi12004-01-012005-12-192007-03-121.97  3.19  2.25  2.25  521.28e+071CA10000mobile0010000000c:181630011002.5 1acquired2e+03       mobilemobile
114       NY40.7-74   10011c:14345New YorkPeek & Co02007-11-012013-02-222008-01-012011-08-120.167 3.78  3.84  6.12  626.26e+053NY01000mobile0010000000c:143451010001   1closed2.01e+03mobilemobile
591       MA42.4-71.1 2139c:33416CambridgeBluefin Labs12008-06-012008-04-012012-01-24-0.167 3.65  4.15  4.68  1242.04e+073MA00100analytics0000000001c:334160111003.751acquired2.01e+03other_categoryother_category
701       CA37.4-122   95134c:40147San JoseC2 Microsystems02004-01-012012-11-052009-10-122009-10-125.78  5.78  2     2     111e+07       1CA10000hardware0000000001c:401471000003   1closed2e+03       other_categoryother_category
978       CA37.4-122   94301c:62269Palo AltoGoPollGo12011-01-012011-07-272011-07-270.567 0.567 0.567 2.35  514.25e+053CA10000web0100000000c:622690100002   1acquired2.01e+03webweb
201       CA36  -115   95066c:16273Scotts ValleyMultigig12003-01-012008-05-122010-12-225.36  7.98  5.25  5.25  533.79e+071CA10000semiconductor0000000001c:162731001103   1acquired2e+03       other_categoryother_category
665       CA32.8-117   92037c:38196La JollaOrtiva Wireless12004-01-012005-02-012011-10-041.09  7.76  6.88  6.88  954e+07       1CA10000mobile0010000000c:381961011104   1acquired2e+03       mobilemobile
897       CA34  -118   90245c:5411El SegundoSometrics12007-09-012008-05-142009-10-160.701 2.13  2.4   4.05  1035.55e+064CA10000games_video0000010000c:54110011003   1acquired2.01e+03games_videogames_video
899       CA37.8-122   94107c:54465San FranciscoKima Labs12010-01-012010-08-012010-08-010.581 0.581 0     2.13  317.7e+05 3CA10000mobile0010000000c:544650100006   1acquired2.01e+03mobilemobile
15       CA40.7-74   94111c:1042San FranciscoWhiskey Media12007-10-012009-03-242009-12-311.48  2.25  2.25  2.25  624e+06       1CA10000web0100000000c:10421000001   0acquired2.01e+03webweb
270       VA38.9-77.2 22102c:1756McLeanJobfox12004-03-012005-04-012009-12-241.08  5.82  6.35  9.44  1444.2e+07 4VA00001web0100000000c:17560011102.331acquired2e+03       webweb
679       CA33.6-118   92656c:39101Aliso ViejoGaikai12008-11-012010-01-052011-07-201.18  2.72  2.52  3.67  2134.5e+07 3CA10000games_video0000010000c:391010011103.671acquired2.01e+03games_videogames_video
961       CA37.8-122   94110c:60186San FranciscoBlue Buzz Network02006-01-012013-06-012010-07-132010-07-134.53  4.53  5.53  5.53  111.31e+061CA10000news0000000001c:601861000004   1closed2.01e+03other_categoryother_category
1.04e+03OR45.5-123   97224c:74341PortlandMax-Viz12001-01-012008-01-012008-01-017     7     7.67  7.67  313e+06       1OR00001hardware0000000001c:743410010003   0acquired2e+03       other_categoryother_category
686       CA37.5-122   94085c:3950SunnyvaleCotendo12008-01-012008-01-012011-06-150     3.45  2.02  3.98  943.6e+07 3CA10000software1000000000c:39500011113   1acquired2.01e+03softwaresoftware
965       CA37.4-122   94301-1705c:60457Palo AltoParticle Code12010-05-012010-06-302010-06-300.164 0.164 1.48  1.48  313e+06       1CA10000software1000000000c:604571000001   0acquired2.01e+03softwaresoftware
1.07e+03CA37.8-122   94103c:7748San FranciscoFlowgram02007-06-012008-06-112008-01-312008-01-310.668 0.668 0.797 5.28  111.3e+06 3CA10000web0100000000c:77480100008   1closed2.01e+03webweb
628       AR34.7-92.3 72201c:35903Little RockJavaJobs01997-01-012012-11-032006-10-012006-10-019.75  9.75  9.75  9.75  115e+04       1AR00001software1000000000c:359031000001   0closed2e+03       softwaresoftware
1.03e+03NY40.7-74   10012c:714New YorkBehance12006-02-012012-05-142012-05-146.28  6.28  5.75  7.31  1516.5e+06 3NY01000web0100000000c:7140010008   1acquired2.01e+03webweb
1.12e+03MA42.4-71.1 2142c:90087CambridgeLocu12011-01-012011-09-072012-04-230.682 1.31  0.329 2.59  524.6e+06 2MA00100advertising0000100000c:900870110009   1acquired2.01e+03advertisingadvertising
1.14e+03MA42.4-71.3 2451c:9373WalthamdynaTrace software12005-01-012007-02-152011-01-072.12  6.02  2     6.51  532.19e+072MA00100software1000000000c:93731011001.671acquired2e+03       softwaresoftware
209       NY40.7-74   10010c:16343New YorkSocialbomb12008-06-052008-12-012008-12-010.49  0.49  1.18  1.18  612.4e+05 1NY01000games_video0000010000c:163430100002   1acquired2.01e+03games_videogames_video
99       CA32.9-117   92130c:13734San DiegoImagine Communications12005-01-012005-01-012010-04-200     5.3   5     5     1743.47e+071CA10000software1000000000c:137341011002.251acquired2e+03       softwaresoftware
706       IL41.8-88.1 60188c:4060LisleUniva UD12004-05-102005-08-012010-03-231.23  5.87  3.65  6.7   443.3e+07 2IL00001software1000000000c:40601011105.331acquired2e+03       softwaresoftware
936       NY40.8-74   10013c:58420New YorkTutorspree02010-09-012013-09-082011-12-202013-02-181.3   2.47  0     2.47  321.8e+06 2NY01000education0000000001c:584201100005   1closed2.01e+03other_categoryother_category
1.09e+03CO40  -105   80302c:815BoulderOneRiot12006-01-012006-01-012009-08-270     3.65  3.15  5.31  1432.73e+074CO00001advertising0000100000c:8150011103   1acquired2.01e+03advertisingadvertising
726       CA37.4-122   94303c:42112Palo AltoMoonshoot02007-01-012012-02-012010-02-182012-04-013.13  5.25  3.13  3.54  626.76e+062CA10000web0100000000c:421121000001.5 1closed2.01e+03webweb
191       CA37.3-122   95014c:16178CupertinoArcSight12000-01-012000-01-012006-06-300     6.5   0.337 10     2432.69e+073CA10000software1000000000c:161780011106   1acquired2e+03       softwaresoftware
347       CA37.6-122   94410c:208San MateoOodle12004-01-012006-05-012010-09-032.33  6.68  6.96  8.93  1742.31e+073CA10000social0000000001c:2081011102   1acquired2e+03       other_categoryother_category
28       CA37.8-122   94103c:1078San FranciscoThe Climate Corporation12006-01-012007-01-012012-06-141     6.45  6.53  7.01  2841.09e+082CA10000cleantech0000000001c:10780011107.5 1acquired2.01e+03other_categoryother_category
181       CA37.4-122   94041c:1600Mountain ViewKosmix12005-01-012005-11-012008-12-080.833 3.94  3.48  7.67  2645.5e+07 5CA10000web0100000000c:16000011112.751acquired2e+03       webweb
53       NY40.7-74   10003c:12071New YorkXtify Inc.12009-04-012010-05-012012-02-071.08  2.85  1.61  4.51  925.69e+063NY01000mobile0010000000c:120710010002   0acquired2.01e+03mobilemobile
414       CA37.7-122   94080c:24681South San FranciscoLimerick BioPharma02004-01-012013-06-012008-06-112012-01-304.45  8.08  6.59  6.59  464.9e+07 1CA10000biotech0000000100c:246811010103   1closed2e+03       biotechother_category
157       TX29.7-95.4 77027c:15509HoustonRudder02006-10-012010-11-052008-01-152008-01-151.29  1.29  7.12  7.12  312e+06       1TX00010web0100000000c:155090010001   0closed2.01e+03webweb
879       NY40.8-74   10001c:52378New YorkPanvidea12007-01-012010-03-192010-03-193.21  3.21  3     4.62  512.7e+06 2NY01000games_video0000010000c:523780010002   1acquired2.01e+03games_videogames_video
228       WI43.1-89.5 53562c:167MiddletonSway02004-12-032012-12-022010-01-192010-01-195.13  5.13  3.16  8.51  612e+06       2WI00001advertising0000100000c:1670010002   0closed2e+03       advertisingadvertising
284       NY40.7-74   10018c:17758New YorkTRAFFIQ12006-09-062006-09-062010-08-100     3.93  2.92  5.73  1631.8e+07 3NY01000advertising0000100000c:177581011002.331acquired2.01e+03advertisingadvertising
1.1e+03 WA47.8-122   98021c:8339BothellDexterra12000-01-012005-08-172008-10-025.63  8.76  8.5   8.76  951.22e+082WA00001mobile0010000000c:83391000115.6 1acquired2e+03       mobilemobile
352       CA37.7-122   94107c:21343San FranciscoCoTweet12009-01-012009-07-092009-07-090.518 0.518 0.581 4.53  911.1e+06 2CA10000advertising0000100000c:213430010006   1acquired2.01e+03advertisingadvertising
721       MA42.5-71.2 1803c:41747BurlingtonReef Point Systems01998-01-012008-06-252005-04-012007-03-237.25  9.23  6     6     135.2e+07 1MA00100security0000000001c:417471001002.671closed2e+03       other_categoryother_category
557       CA37.4-122   94089c:31549SunnyvaleParacor Medical01999-01-012012-06-172007-06-292007-06-298.5   8.5   9.01  9.01  514.4e+07 1CA10000biotech0000000100c:315490000018   1closed2e+03       biotechother_category
589       CA37.6-122   94404c:33198San FranciscoCausata12009-01-012009-10-052011-11-010.759 2.83  0.759 3.84  1221.55e+072CA10000software1000000000c:331980011001   1acquired2.01e+03softwaresoftware
462       CA37.4-122   95054c:26702Santa ClaraAsempra Technologies12003-01-012006-02-132006-02-133.12  3.12  4     4     412e+07       1CA10000security0000000001c:267020001003   1acquired2e+03       other_categoryother_category

5.3.1 Milestone

# find the average age for the first milestones for successful and unsuccessful companies
means_first_milestone <- startup_data %>%
  group_by(status) %>%
  summarise(means = mean(age_first_milestone_year, na.rm = TRUE))
## `summarise()` ungrouping output (override with `.groups` argument)
# extract the values
means_first_milestone_acquired <- means_first_milestone$means[1]
means_first_milestone_closed <- means_first_milestone$means[2]

# find the average age for the last milestones for successful and unsuccessful companies
means_last_milestone <- startup_data %>%
  group_by(status) %>%
  summarise(means = mean(age_last_milestone_year, na.rm = TRUE))
## `summarise()` ungrouping output (override with `.groups` argument)
# extract the values
means_last_milestone_acquired <- means_last_milestone$means[1]
means_last_milestone_closed <- means_last_milestone$means[2]

# define categories names for plots (do at beginning @Rick ?)
categories_names <- c("Advertising", "E-Commerce", "Games & Video", "Mobile", "Other", "Software", "Web")
names(categories_names) <- c("advertising", "ecommerce", "games_video", "mobile", "other", "software", "web")
# create plot for first milestones
plot_time1 <- startup_data %>%
  filter(category2 != "other_category") %>%
  ggplot(aes(x = age_first_milestone_year, fill = status)) +
  geom_density(alpha = 0.5, color = "grey") +
  geom_vline(aes(xintercept = means_first_milestone_acquired),   
               color = "#4aaec0", linetype = "dotted", size = 0.5) +  
  geom_vline(aes(xintercept = means_first_milestone_closed), 
               color = "#ff5828", linetype = "dotted", size = 0.5) +  
  facet_wrap(~category2, ncol = 2, scales = "free_y", labeller = labeller(category2 = categories_names)) +
  scale_x_continuous(limits = c(-2, 10)) +
  scale_color_manual(values = c("#4aaec0", "#ff5828")) +
  scale_fill_manual(values = c("#4aaec0", "#ff5828"), name = "Status", labels = c("Aquired (mean age 3.52)", "Closed (mean age 2.57)")) +  
  theme_minimal() +
  labs(title = "Successful start-ups reach their first milestones later in most industries",
       subtitle = "Distribution of age when reaching first milestone",
       y = "",
       x = "Age of start-ups when reaching their first milestones") +
  NULL

plot_time1
## Warning: Removed 9 rows containing non-finite values (stat_density).

# create plot for last milestones (not in presentation)
plot_time2 <- startup_data %>%
  filter(category2 != "other_category") %>%
  ggplot(aes(x = age_last_milestone_year, fill = status), legend.position=FALSE) +
  geom_density(alpha = 0.5, color = "grey") +
  geom_vline(aes(xintercept = means_last_milestone_acquired),   
               color = "#4aaec0", linetype = "dotted", size = 0.5) +  
  geom_vline(aes(xintercept = means_last_milestone_closed),   
               color = "#ff5828", linetype = "dotted", size = 0.5) +  
  facet_wrap(~category2, ncol = 2, scales = "free_y", labeller = labeller(category2 = categories_names)) +
  scale_x_continuous(limits = c(-2, 15)) +
 scale_color_manual(values = c("#4aaec0", "#ff5828")) +
  scale_fill_manual(values = c("#4aaec0", "#ff5828"), name = "Status", labels = c("Aquired (mean age 5.38)", "Closed (mean age 3.58)")) +
  theme_minimal() +
  labs(title = "Successful start-ups reach their last milestones later in most industries",
       subtitle = "Distribution of age when reaching first milestone",
       y = "",
       x = "Age of start-ups when reaching last milestones") +
  NULL

 plot_time2
## Warning: Removed 1 rows containing non-finite values (stat_density).

From the graphs it looks like that for most categories, companies that were closed reached their first milestone before those that were acquired. The only exception is the software category. We conduct a t-test to understand the following question: Do successful start-ups reach their first milestone earlier than unsuccessful ones?

# boxplot to visualise
milestone_plot <- ggplot(startup_data, aes(y = status, x = (age_first_milestone_year))) +
  geom_boxplot(aes(color = status), width = 0.3, show.legend = FALSE) +
  geom_jitter(aes(color = status), alpha = 0.5, show.legend = FALSE, position = position_jitter(width = 0.2, seed = 0)) +
  scale_color_manual(values = c("#4aaec0", "#ff5828")) +
  theme_minimal() +
  labs(title = "Which start-ups reach their first milestone first?",
       subtitle = "Age of start-ups when reaching their first milestones",
       y = "Status",
       x = "Age of first milestone")

milestone_plot

# conduct the t-test
test_ms_first <- t.test(age_first_milestone_year ~ status, 
        data = startup_data) 

test_ms_first
## 
##  Welch Two Sample t-test
## 
## data:  age_first_milestone_year by status
## t = 3.7467, df = 308.84, p-value = 0.0002138
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.4490103 1.4422713
## sample estimates:
## mean in group acquired   mean in group closed 
##               3.515040               2.569399
test_ms_first_tidy <- tidy(test_ms_first) %>% 
  # calculate the difference in means
  mutate(estimate = estimate1 - estimate2) %>%
  # rearrange columns
  select(starts_with("estimate"), everything())

test_ms_first_tidy
estimateestimate1estimate2statisticp.valueparameterconf.lowconf.highmethodalternative
0.9463.522.573.750.0002143090.4491.44Welch Two Sample t-testtwo.sided
# conduct the t-test
test_ms_last <- t.test(age_last_milestone_year ~ status, 
        data = startup_data) 

test_ms_last
## 
##  Welch Two Sample t-test
## 
## data:  age_last_milestone_year by status
## t = 6.6406, df = 315.69, p-value = 1.365e-10
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  1.270540 2.340403
## sample estimates:
## mean in group acquired   mean in group closed 
##               5.384223               3.578751
test_ms_last_tidy <- tidy(test_ms_last) %>% 
  # calculate the difference in means
  mutate(estimate = estimate1 - estimate2) %>%
  # Rrarrange columns
  select(starts_with("estimate"), everything())

test_ms_last_tidy
estimateestimate1estimate2statisticp.valueparameterconf.lowconf.highmethodalternative
1.815.383.586.641.37e-103161.272.34Welch Two Sample t-testtwo.sided

The test shows that there is a significant difference for the first funding year between successful and unsuccessful start-ups. We can reject the null hypothesis at the 2% level. The same confirms for reaching the last milestones

Hence, successful start-ups usually reach their first milestone later. Thus, for our start-up, we will aim not to rush reaching our first milestone and will take its time.

So, when do we have to reach our first milestone? On average we should reach our first milestone after 3.362

However, since we defined before that we would like to go into the mobile industry, we will look at the mean there as well for first and last mile stones:

ideal_category <- "mobile"

means_first_milestone_category <- startup_data %>%
  filter(category2 == ideal_category) %>% # depending on which industry we want to go in 
  group_by(category2, status) %>%
  summarise(means_category = mean(age_first_milestone_year, na.rm = TRUE),
            sd_category = sd(age_first_milestone_year, na.rm = TRUE)) %>%
  arrange(desc(means_category))
## `summarise()` regrouping output by 'category2' (override with `.groups` argument)
means_first_milestone_category
## # A tibble: 2 x 4
## # Groups:   category2 [1]
##   category2 status   means_category sd_category
##   <chr>     <chr>             <dbl>       <dbl>
## 1 mobile    acquired           3.45        2.52
## 2 mobile    closed             1.71        1.65
means_last_milestone_category <- startup_data %>%
  filter(category2 == ideal_category) %>% # depending on which industry we want to go in 
  group_by(category2, status) %>%
  summarise(means_category = mean(age_last_milestone_year, na.rm = TRUE),
            sd_category = sd(age_last_milestone_year, na.rm = TRUE)) %>%
  arrange(desc(means_category))
## `summarise()` regrouping output by 'category2' (override with `.groups` argument)
means_last_milestone_category
## # A tibble: 2 x 4
## # Groups:   category2 [1]
##   category2 status   means_category sd_category
##   <chr>     <chr>             <dbl>       <dbl>
## 1 mobile    acquired           5.79        3.12
## 2 mobile    closed             3.13        2.67
ideal_first_milestone_age <- means_first_milestone_category$means_category[1]  
ideal_last_milestone_age <- means_last_milestone_category$means_category[1] 

print(paste0("Target age for our first milestone: ", round(ideal_first_milestone_age, 2), " years"))
## [1] "Target age for our first milestone: 3.45 years"
print(paste0("Target age for our last milestone: ", round(ideal_last_milestone_age, 2), " years"))
## [1] "Target age for our last milestone: 5.79 years"

5.3.2 Funding

After looking at the target age for milestones, we also look at the target age for different funding rounds.

# find the average age for the first funding for successful and unsuccessful companies
means_first_funding <- startup_data %>%
  group_by(status) %>%
  summarise(means = mean(age_first_funding_year, na.rm = TRUE))
## `summarise()` ungrouping output (override with `.groups` argument)
# extract the values
means_first_funding_acquired <- means_first_funding$means[1]
means_first_funding_closed <- means_first_funding$means[2]

# find the average age for the last milestones for successful and unsuccessful companies
means_last_funding <- startup_data %>%
  group_by(status) %>%
  summarise(means = mean(age_last_funding_year, na.rm = TRUE))
## `summarise()` ungrouping output (override with `.groups` argument)
# extract the values
means_last_funding_acquired <- means_last_funding$means[1]
means_last_funding_closed <- means_last_funding$means[2]
# same thing as above
plot_time3 <- startup_data %>%
  filter(category2 != "other_category") %>%
  ggplot(aes(x = age_first_funding_year, fill = status)) +
  geom_density(alpha = 0.5, color = "grey") +
  geom_vline(aes(xintercept = means_first_funding_acquired), 
               color = "#4aaec0", linetype = "dotted", size = 0.5) +  
  geom_vline(aes(xintercept = means_first_funding_closed), 
               color = "#ff5828", linetype = "dotted", size = 0.5) +  
  facet_wrap(~category2, ncol = 2, scales = "free_y", labeller = labeller(category2 = categories_names)) +
  scale_x_continuous(limits = c(-2, 10)) +
  scale_color_manual(values = c("#4aaec0", "#ff5828")) +
  scale_fill_manual(values = c("#4aaec0", "#ff5828"), name = "Status", labels = c("Aquired (mean age 2.00)", "Closed (mean age 2.21)")) +
  theme_minimal() +
  labs(title = "Successful start-ups reach their first funding later in most industries",
       subtitle = "Age of start-ups when reaching their first funding",
       y = "",
       x = "Age when reaching first funding") +
  NULL

plot_time3
## Warning: Removed 2 rows containing non-finite values (stat_density).

# plot last funding age
plot_time4 <- startup_data %>%
  filter(category2 != "other_category") %>%
  ggplot(aes(x = age_last_funding_year,fill = status)) +
  geom_density(alpha = 0.5, color = "grey") +
  geom_vline(aes(xintercept = means_last_funding_acquired),  #check this again please 
               color = "#4aaec0", linetype = "dotted", size = 0.5) +  
  geom_vline(aes(xintercept = means_last_funding_closed),  #check this again please 
               color = "#ff5828", linetype = "dotted", size = 0.5) +  
  facet_wrap(~category2, ncol = 2, scales = "free_y", labeller = labeller(category2 = categories_names)) +
  scale_x_continuous(limits = c(-2, 15)) +
  scale_color_manual(values = c("#4aaec0", "#ff5828")) +
  scale_fill_manual(values = c("#4aaec0", "#ff5828"), name = "Status", labels = c("Aquired (mean age 4.03)", "Closed (mean age 3.45)")) +
  theme_minimal() +
  labs(title = "Successful start-ups reach their last funding later in most industries",
       subtitle = "Age of start-ups when reaching their last funding",
       y = "",
       x = "Age of last funding") +
  NULL

 plot_time4
## Warning: Removed 1 rows containing non-finite values (stat_density).

test_fg_first <- t.test(age_first_funding_year ~ status, 
        data = startup_data) 
test_fg_first
## 
##  Welch Two Sample t-test
## 
## data:  age_first_funding_year by status
## t = -0.92373, df = 274.25, p-value = 0.3564
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.6499106  0.2347907
## sample estimates:
## mean in group acquired   mean in group closed 
##               2.006359               2.213919
test_fg_first_tidy <- tidy(test_fg_first) %>% 
  # Calculate difference in means, since t.test() doesn't actually do that
  mutate(estimate = estimate1 - estimate2) %>%
  # Rearrange columns
  select(starts_with("estimate"), everything())

test_fg_first_tidy
estimateestimate1estimate2statisticp.valueparameterconf.lowconf.highmethodalternative
-0.2082.012.21-0.9240.356274-0.650.235Welch Two Sample t-testtwo.sided
test_fg_last <- t.test(age_last_funding_year ~ status, 
        data = startup_data) 
test_fg_last
## 
##  Welch Two Sample t-test
## 
## data:  age_last_funding_year by status
## t = 2.1632, df = 298.16, p-value = 0.03132
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.05168556 1.09350923
## sample estimates:
## mean in group acquired   mean in group closed 
##               4.031064               3.458466
test_fg_last_tidy <- tidy(test_fg_last) %>% 
  # Calculate difference in means, since t.test() doesn't actually do that
  mutate(estimate = estimate1 - estimate2) %>%
  # Rearrange columns
  select(starts_with("estimate"), everything())

test_fg_last_tidy
estimateestimate1estimate2statisticp.valueparameterconf.lowconf.highmethodalternative
0.5734.033.462.160.03132980.05171.09Welch Two Sample t-testtwo.sided

However, at the 2%, there is no difference in age for the first funding between successful and unsuccessful start-ups. The same occurs for the last funding round age.

Based on this, we will just take the average funding

ideal_category <- "mobile"

means_first_funding_category <- startup_data %>%
  filter(category2 == ideal_category) %>% # depending on which industry we want to go in 
  summarise(means_category = mean(age_first_funding_year, na.rm = TRUE),
            sd_category = sd(age_first_funding_year, na.rm = TRUE)) %>%
  arrange(desc(means_category))

means_first_funding_category
means_categorysd_category
1.631.66
means_last_funding_category <- startup_data %>%
  filter(category2 == ideal_category) %>% # depending on which industry we want to go in 
  summarise(means_category = mean(age_last_funding_year, na.rm = TRUE),
            sd_category = sd(age_last_funding_year, na.rm = TRUE)) %>%
  arrange(desc(means_category))

means_last_funding_category
means_categorysd_category
3.962.7
ideal_first_funding_age <- means_first_funding_category$means_category[1]  
ideal_last_funding_age <- means_last_funding_category$means_category[1] 

print(paste0("Target age for our first funding: ", round(ideal_first_funding_age, 2), " years"))
## [1] "Target age for our first funding: 1.63 years"
print(paste0("Target age for our last funding: ", round(ideal_last_funding_age, 2), " years"))
## [1] "Target age for our last funding: 3.96 years"

5.3.3 Timeline

With all these insights gained, we will now create a basic overview for our milestones and funding rounds that we are aiming to reach with our start-up.

# create a new dataframe with the dates, assuming we will start our start-up today
date_founded_at <- today ()
date_first_funding <- today() + ideal_first_funding_age * 365
date_last_funding <- today() + ideal_last_funding_age * 365
date_first_milestone <- today() + ideal_first_milestone_age * 365
date_last_milestone <- today() + ideal_last_milestone_age * 365

milestone <- c("Foundation", "First funding", "Last funding", "First milestone", "Last milestone")
date <- c(date_founded_at, date_first_funding, date_last_funding, date_first_milestone, date_last_milestone)
category <- c("Foundation", "Funding", "Funding", "Milestone", "Milestone")
position <- c(0.05, 0.05, 0.05, 0.05, 0.05)
direction <- c(0.2, 0.2, 0.2, 0.2, 0.2)

start_up_timeline <- data.frame(milestone, date, category, position, direction)

start_up_timeline <- start_up_timeline %>%
  mutate(month = month(date),
         year = year(date))
category_levels <- c("Foundation", "Funding", "Milestone")
category_colors <- c("#1f6e8c", "#ff5828", "#4aaec0")

start_up_timeline$category <- factor(start_up_timeline$category, levels = category_levels, ordered = TRUE)
text_offset <- 0.05

start_up_timeline$month_count <- ave(start_up_timeline$date == start_up_timeline$date, 
                                     start_up_timeline$date, 
                                     FUN = cumsum)
start_up_timeline$text_position <- (start_up_timeline$month_count * text_offset * start_up_timeline$direction) + start_up_timeline$position
month_buffer <- 2

month_date_range <- seq(min(start_up_timeline$date) - months(month_buffer), max(start_up_timeline$date) + months(month_buffer), by = "month")
month_format <- format(month_date_range, "%b")
month_df <- data.frame(month_date_range, month_format)
year_date_range <- seq(min(start_up_timeline$date) - 
                         months(month_buffer), max(start_up_timeline$date) + 
                         months(month_buffer), by = "year")

year_date_range <- as.Date(
  intersect(
        ceiling_date(year_date_range, unit = "year"),
        floor_date(year_date_range, unit = "year")),  
    origin = "1970-01-01")

year_format <- format(year_date_range, '%Y')
year_df <- data.frame(year_date_range, year_format)
# plotting the timeline
timeline_plot<-ggplot(start_up_timeline, 
                      aes(x = date,y = 0, col = category, label = milestone)) +
  scale_color_manual(values = category_colors, labels = category_levels, drop = FALSE) +
  theme_classic() +
  geom_hline(yintercept = 0, color = "black", size = 0.3) +
  geom_segment(data = start_up_timeline[start_up_timeline$month_count == 1,], 
               aes(y = position,yend = 0, xend = date),
               color='black', size=0.2) +
  geom_point(aes(y = 0), size = 3) +
  theme(axis.line.y = element_blank(),
        axis.text.y = element_blank(),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        axis.line.x = element_blank(),
        legend.position = "bottom") +
  geom_text(data = month_df, 
            aes(x = month_date_range, y = -0.01, label = month_format),
            size = 2.5, vjust = 0.5, color = 'black', angle = 90) + 
  geom_text(data = year_df, 
            aes(x = year_date_range, y = -0.03, label = year_format, fontface = "bold"),
            size = 4, color = 'black') +
  geom_text(aes(y = text_position, label = milestone, fontface = "bold"),size = 2.5) +
  labs(title = "When should we aim to reach our milestones and funding rounds?",
       subtitle = "Timeline for our start-up",
       col = "Milestones",
       y = "",
       x = "") +
  NULL

timeline_plot

6 Prediction

model: Predict a startup’s future based on its current characteristics data modelling to select the features that might influence startups funding and outcomes. ### Logistic regression to predict status

startup_data_select <- startup_data %>%
  mutate(status = ifelse(status == "acquired", 1, 0))
# we select only the relevant variables
set.seed(1212)

train_test_split <- initial_split(startup_data_select, prop = 0.8) #training set contains 80% of the data

# Create the training and testing datasets
training <- training(train_test_split)
testing <- testing(train_test_split)

just playing around with the model (will tune further if necessary)

status_logreg <- glm(status ~ 
                           avg_participants + 
                           age_first_milestone_year + 
                           age_last_milestone_year + 
                           year_founded +
                           relationships + 
                           funding_rounds +
                           log(funding_total_usd) +
                           is_mobile +
                           is_ca +
                           milestones, data = training, family = "binomial")
summary(status_logreg)
## 
## Call:
## glm(formula = status ~ avg_participants + age_first_milestone_year + 
##     age_last_milestone_year + year_founded + relationships + 
##     funding_rounds + log(funding_total_usd) + is_mobile + is_ca + 
##     milestones, family = "binomial", data = training)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -3.3437  -0.8400   0.5005   0.8073   1.6383  
## 
## Coefficients:
##                            Estimate Std. Error z value Pr(>|z|)    
## (Intercept)              -221.42859  104.43903  -2.120  0.03399 *  
## avg_participants            0.10099    0.06008   1.681  0.09278 .  
## age_first_milestone_year   -0.15523    0.09269  -1.675  0.09398 .  
## age_last_milestone_year     0.27542    0.09218   2.988  0.00281 ** 
## year_founded                0.10817    0.05179   2.089  0.03674 *  
## relationships               0.15071    0.03021   4.988 6.09e-07 ***
## funding_rounds             -0.06560    0.08938  -0.734  0.46303    
## log(funding_total_usd)      0.24927    0.07840   3.179  0.00148 ** 
## is_mobile                  -0.50228    0.34966  -1.436  0.15086    
## is_ca                      -0.01648    0.20644  -0.080  0.93636    
## milestones                 -0.17043    0.15787  -1.080  0.28034    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 713.77  on 594  degrees of freedom
## Residual deviance: 590.61  on 584  degrees of freedom
## AIC: 612.61
## 
## Number of Fisher Scoring iterations: 5

7 try with LASSO maybe?